text: 25610 to all proposers on the above project: please note contents herein and affix (paste or staple) to proposal documents you. How to give feedback • It should look like an actual conference review: • Summary of the paper/project • Some positive feedback about what is done well • Some constructive criticism about what needs to be improved. Stochastic Convergence Barnabás Póczos. w cciebrut tri el Ly ka CMU. 来了CMU，怎么能不选CS课程对吧~建议选修的CS院data相关课程： 10601/10701：Introduction to Machine Learning，10601是master级别的（偏码，老师是'郭美丽'，下面是Annamiss同学对这两门课的详细介绍：. The Company’s Construction Materials (“CM”) segment focuses on the sale of high quality fly ash as a partial replacement for Portland cement when making concrete. 2 Contents Motivation PCA algorithms Applications Some of these slides are taken from. Title: Microsoft Word - 外籍人士所得稅扣繳注意事項(10701-2). Exam 2012, answers 10701 HW5 v3 - Its Homework 5 assignment for the class in Spring 2017 Hw5 sol - Its Homework 5 assignment solutions for the class in Spring 2017 Main sol - Its Homework 4 assignment for the class in Spring 2017 Main - Its Homework 4 assignment solution for the class in Spring 2017 Hw3 sol - Its Homework 3 assignment for the class in Spring 2017. It's also available for hockey, basketball and baseball. 如果给你一个硬币，投这个硬币有\theta的概率抛出Head，有(1-\theta)的概率抛出Tail。如果在未来抛了五次这个硬币，有三次是Head，有两次是Tail，这个\theta最有可能是多少呢？. Session cookies are used in Mailman's private archive interface so that you don't need to re-authenticate with every operation. Date: 2017-06-06. del VALLE LA HISTORIA do so TAIlgo -U STO Y Nty U N A A 0 D E C I N E F I A N C E 5 OM V114111 AM NIAN PARIS enero, 1940. 10701 Folsom Blvd, Rancho Cordova, CA 95670 is a Store, Retail Outlet property with -- bedrooms, -- bathrooms, and is approximately 14,710 sq feet of living space. Andrew Y Ng. The proposed approach includes image texture computation for image feature extraction and a piecewise linear. 3 David Ln APT 2U, Yonkers, NY is a multi family home that contains 550 sq ft and was built in 1973. Introduction to Machine Learning | CMU 10701; CS231n Convolutional Neural Networks for Visual Recognition; 博客. Assignment 3 Solutions Andrew Cmu Free Similar PDF's. ; Rogers, J. Instructor: Nathan Urban; Location: Scaife 125; Days/Times: T/R 9:00AM to 10:20AM (Additional Lecture for Grad Students Thurs 4:30-5:50PM in MI 355). Motivation 2. 2019 Apr 6;17(4). In India the scenario is at a very different platform. 85 1042378004 134911 | May 5 1998 4. pdf), Text File (. Tom Mitchell and Andrew W. 在CMU里存在着4门都属于Intro to Machine Learning的课，对应着各种level的学生，分别为：这学期新开的undergrad 10-401，master 10-601，PhD 10-701和10-715。 虽然10-701和10-715都是PhD level，但区别在于10-715是开设给在ML方向的PhD，而10-701是给研究方向不是ML的PhD，或者ML的master。. The Sun /Saturday, December 2, 2017 www. 11 ¡ Clustering in two dimensions looks easy ¡ Clustering small amounts of data looks easy ¡ And in most cases, looks are not deceiving ¡ Many applications involve not 2, but 10 or 10,000 dimensions ¡ High-dimensional spaces look different: Almost all pairs of points are very far from each other --> The Curse of Dimensionality! 1/22/20 Jure Leskovec, Stanford CS246: Mining Massive Datasets. cmu也可以有生活，平日里可以唱歌，打牌，吃火锅（虽然不及ucsd同学的冲浪），还有和玩一样的onsite，只要你想有生活，你就可以随时有生活。 [ps当然浪多了有时候还是要熬夜的，不过我这学期就熬过一次] 2. Instructors: Sandra Kuhlman; Date/Time/Location: Tues & Thurs 9:00 AM – 10:20 AM (CMU Scaife Hall 125), Thurs 4:30 PM – 5:50 PM (Mellon Institute 355). Stochastic Convergence Barnabás Póczos. edu Laura Tipton7 8 Department of Computational 9 & Systems Biology 10 University of Pittsburgh 11 Pittsburgh, PA 15213 [email protected] The course will take a seminar format. notice addendum no. txt) or read book online for free. The Company’s Construction Materials (“CM”) segment focuses on the sale of high quality fly ash as a partial replacement for Portland cement when making concrete. edu) School Of Computer Science, Carnegie Mellon University. So, is there any current or forthcoming support for egging from Maya 2012? Thanks!. csail and there are afew more US varsities. This skill test is specially designed for you to. Time and Location: Monday and Wednesday, 10:30-11:50 (GHC 4307). edu12 13 Abstract14. Independent Learner course categories Courses on this page are for Independent Learners students who don't have a teacher and a Course Key courses are self-paced and self-guided no instructors will monitor your progress OLI doesn't grant scores or credit for completion Independent Learner course categories. Directory List Lowercase. -2013- I am TAing fall 2013 offering of 10701 (Machine Learning) with Geoff Gordon and Alex Smola. URL List - Free ebook download as Text File (. 【マークス公式】法人のお客さま専用BtoBサイトです。多彩なマークスの商品をオンライン上でご注文いただけます。カタログとしてもご利用いただけるほか、簡単に在庫の確認もできます。ダイアリー(8月下旬～出荷). Keep following Piazza for any updates relevant to the course. Calculus SJTU. All who love to watch TV, especially sports, this is the right blog for you. # # 0x5b = x^7 +x^5 +x^4 +x^2 +x +1 (0xb7) bits=5 8 0x5b 0 0 17 0 92 9 0x5b 0 0 24 0 141 10 0x5b 0 0 34 0 207 11 0x5b 0 0 46 0 300 12 0x5b 0 0 60 0 432 13 0x5b 0 0 75 0 617 14 0x5b 0 0 93 0 865 15 0x5b 0 0 114 0 1188 16 0x5b 0 0 137 0 1613 17 0x5b 0 0 164 0 2155 18 0x5b 0 0 197 0 2821 19 0x5b 0 0 235 0 3650 20 0x5b 0 0 277 0 4683 21 0x5b 0 0. The bank has most branches in California, New York, Texas, Florida and Illinois. Trí tuệ nhân tạo hay trí thông minh nhân tạo (Artificial intelligence hay Machine intelligence - AI) là một ngành thuộc lĩnh vực khoa học máy tính (Computer science). This schedule is tentative and subject to change. 2020 Best Master's of Computer Science Programs Posted on January 12, 2020 January 12, 2020 by TFE Times Posted in Rankings Tagged 2017 , 2018 , best , chool , cience , computer , mater , of , program , rankings , s , schools , science , top. CMU-10701 8. 3390/md17040215. Reading listed for each lecture is not mandatory unless otherwise specified. in mathematical science and computer science Other Skills Expert knowledge of C ++. 办公室: 电院5号楼407. python (CMU 15112) Algorithms and advanced data structure (CMU 02613) Basic data analysis courses: INFSCI 2725 Data Analytics BIOST 2036 - INTRODUCTION TO HEALTH DATA SCIENCE INFSCI 2160 Data Mining INFSCI 2710 Database Management. Directory List Lowercase. In this case, even though the likelihood reaches the maximum when p (head)=0. 2 Contents Markov Chain Monte Carlo Methods Sampling • Rejection • Importance • Hastings-Metropolis • Gibbs Markov Chains • Properties Particle Filtering. 4 - CRC Examples, the value is outlined as a word sent or received and therefore the CRC bits are mapped into the CRC word according to. 0: A: MWF: 10:30AM. Scribd is the world's largest social reading and publishing site. This is a one-year, two-semester professional masters degree program that emphasizes statistical practice, methods, data analysis and practical workplace skills. edu Linear Regression Support Vector Machines Logistic Regression Artificial Neural Network Linear Regression Decision Support K –Means Clustering. 在CMU学习10701 Machine learning是种怎样的体验 我来答 新人答题领红包. edu Abstract Automated speaker recognition has become increasingly popular to aid in crime investigations and authorization processes with the advances in computer science. Exam 2012, answers 10701 HW5 v3 - Its Homework 5 assignment for the class in Spring 2017 Hw5 sol - Its Homework 5 assignment solutions for the class in Spring 2017 Main sol - Its Homework 4 assignment for the class in Spring 2017 Main - Its Homework 4 assignment solution for the class in Spring 2017 Hw3 sol - Its Homework 3 assignment for the class in Spring 2017. (D) Two-layered network that is similar to the model in (C) but with an additional fully connected layer. Includes a face chart to help you recreate it at home and a complimentary mascara. Large datasets are difficult to work with for several reasons. Information Theory, Inference, and Learning Algorithms. CMU Machine Learning 10-701 Machine Learning: 12 units (Cross-listed as 15-781 for CS PhD students only. Machine Learning and Artificial Intelligence for Engineers CMU_24787. Stagecoach in Hastings. View 22 photos of this 6 bed, 2 bath, 2,184 Sq. [10701] To see the collection of prior postings to the list, visit the 10701-announce Archives. TA: Hai-Son Le ([email protected] 1 Chemicals Gold (III) chloride trihydrate (HAuCl 4-3H 2 O) and chloroplatinic acid hexahydrate (H 2 PtCl 6-xH. Course: Title: Units: Lec/Sec: Days: Begin: End: Bldg/Room: Location: Instructor(s) Architecture : 48025: First Year Seminar: Architecture Edition I: 3. Box 678 Vestal NY 13851- (607) 770-1010 (607) 798-1898. Thought I’d ask to confirm, though it looks bleak. Moreover, I feel so fortunate to have Robert Tibshirani from Stanford University as my external committee member, who is the founding father of the sparse learning ﬁeld. docx), PDF File (. Fantasy, stage, drag or Halloween looks, brought to life by a highly skilled M·A·C Artist in 90 minutes. 2 Project midway report due. Exam 2012, answers 10701 HW5 v3 - Its Homework 5 assignment for the class in Spring 2017 Hw5 sol - Its Homework 5 assignment solutions for the class in Spring 2017 Main sol - Its Homework 4 assignment for the class in Spring 2017 Main - Its Homework 4 assignment solution for the class in Spring 2017 Hw3 sol - Its Homework 3 assignment for the class in Spring 2017. Introduction to Machine Learning (PhD) Spring 2019, CMU 10701 Lectures: MW, 10:30-11:50pm, Rashid Autorium: 4401 Gates and Hillman Center (GHC) Recitations: F, 10:30-11:50pm, Rashid Autorium: 4401 Gates and Hillman Center (GHC) Instructors:. Lectures: Monday and Wednesday, 12:00PM to 1:20PM Location: Baker Hall A51 Recitations: Tuesdays 5:00PM to 6:00PM Location: Porter Hall 100 (January 22, 2013), Doherty Hall A302 (January 29, 2013 onwards). com/cmu/fall2017/10715. 我个人对于CMU 10701 Spring 2011课程的笔记。课程网址为https. grade B or 05-431 Min. edu Joseph Russino National Robotics Engineering Center. Course: Title: Units: Lec/Sec: Days: Begin: End: Bldg/Room: Location: Instructor(s) Machine Learning : 10301: Introduction to Machine Learning: 12. Bayesian Networks (Structure) Learning. This feature is not available right now. Session cookies are used in Mailman's private archive interface so that you don't need to re-authenticate with every operation. 30pm, 8015 GHC ; Russ: Friday 1. rtf - Free ebook download as (. Introduction to Machine Learning (PhD) Spring 2019, CMU 10701 Lectures: MW, 10:30-11:50pm, Rashid Autorium: 4401 Gates and Hillman Center (GHC) Recitations: F, 10:30-11:50pm, Rashid Autorium: 4401 Gates and Hillman Center (GHC) Instructors:. edu – do not. Cambridge University Press, 2003. 在数据挖掘中，K-Means算法是一种cluster analysis的算法，其主要是来计算数据聚集的算法，主要通过不断地取离种子点最近均值的算法。. Leila Wehbe at Carnegie Mellon University (CMU) in Pittsburgh, Pennsylvania has taught: MLG 10718 - Data Analysis, MLG 10701 - Introduction to Machine Learning (PhD). Time and Location: Monday, Wednesday 1:30 - 2:50pm, GHC 4401 Rashid Auditorium Class Videos: Class videos will be available here. In particular, if I take AP Physics C (both halves), AP Calculus BC, and AP Statistics, and earn 5s on all of them, according to the college-wide AP credit policy, I'd get credit for CMU courses 21120, 21122, 36200, 33141, and 33142 (they are all real CMU courses, not the "AP X" courses). rtf), PDF File (. PRODUCT DESCRIPTION With Davis Colors, concrete products can be produced in a. Colored Concrete Block and Pavers PRODUCT NAME Davis Colors® Color Admixtures for Concrete Masonry Units (CMU), Concrete Pavers, and other colored concrete products. The Wing conducts training operations flying the T-45 Goshawk. csail and there are afew more US varsities. Acknowledgements. File Type PDF Machine Learning Tom Mitchell Solution Exercise Machine Learning Tom Mitchell Solution Exercise Conversational Machine Learning - Tom Mitchell Abstract: If we wish to predict the future of. Program Information. A visual explanation of the trade-off between learning rate and iterations¶. Important: From this point on, you must have cookies enabled in your browser, otherwise you will have to re-authenticate with every operation. Additional Physical Form: Electronic reproduction of copy from George A. It is based on readings of the New Testement from Bible. Please try again later. 36-705 Intermediate Statistics. A repository for CMU 10701 Machine Learning project - hunterhector/ml-10701-project. Select a Benjamin Moore color to see how paint truly transforms a room. The nal course project will provide you the opportunity to explore such an application. Words - Free ebook download as Text File (. Scribd is the world's largest social reading and publishing site. Not all jobs at Google are equal. It provides data to allow building of kaldi ASR models, and Festvox TTS voices in the target languages. Data Structures. K-Means算法主要解决的问题如下图所示。我们可以看到，在图的左边有一些点，我们用肉眼可以看出来有四个点群，但是我们怎么通过计算机程序找出这几个点. Amenities include On-Site Laundry. 提供最有用的出国留学资讯和最热心的留学交流论坛。在BBS上，你可以咨询签证，面试，机经，offer，奖学金，名校专业等，也可以分享雅思、托福、GRE的学习心得。. Click one to get back to what you were watching! No results were found. CMU CSSA BBS. Type a description and hit enter to create a bookmark. Colored Concrete Block and Pavers PRODUCT NAME Davis Colors® Color Admixtures for Concrete Masonry Units (CMU), Concrete Pavers, and other colored concrete products. Choose any full makeup look you want, from lips to lashes. Yu Zhou (MS at CMU), Fall 2012 - Spring 2014. Firstly, AI is not very well pursued anywhere in Indian academia. Mazda reserves the right to change product specifications at any time without incurring obligations. Directory List Lowercase 2. Unfortunately, many smart contracts have had flaws resulting in millions of dollars in losses. Home > Schools > Carnegie Mellon University > Computer Science (CS) > CS 10701 > Lecture- Machine Learning CMU CS 10701 - Lecture- Machine Learning (52 pages). Total Transfers by Request Date %Reqs %Byte Bytes Sent Requests Date ----- ----- ----- ----- |----- 4. Introduction to Regression. 03-763 Advanced Systems Neuroscience: 12 Units [CNBC core course]. If you are for some reason NOT receiving announcements, please let us know. # 0x8e weights computed using reference implementation 1 0x8e 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0x8e 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0. pdf Introduction to the term Deep Learning by this paper. Machinelearningsalon Kit 28-12-2014. eu Sao Paulo 2014 April 4, 2014. No matching sessions. CMU 10701 Spring 2011笔记. 3 David Ln APT 2U, Yonkers, NY is a multi family home that contains 550 sq ft and was built in 1973. It's been a few years since I took 601, and the course has changed a bit since then. 718-349-1221 oraz 984 N. Joyce J Chosky, age 61, Traer, IA 50675 Background Check Known Locations: Yonkers NY 10701, Mamaroneck NY 10543 Possible Relatives: Jean B Chosky, Saul S Chosky. Niv Zehngut (Undergrad at CMU), Spring 2014. Reading listed for each lecture is not mandatory unless otherwise specified. Basic Statistics Barnabs Pczos & Alex Smola Remember the color coding Important Not. Overview. Introduction to Machine Learning CMU-10701 2. A!O CXVIII DIARIO DE LA MARINA. Leila Wehbe at Carnegie Mellon University (CMU) in Pittsburgh, Pennsylvania has taught: MLG 10718 - Data Analysis, MLG 10701 - Introduction to Machine Learning (PhD). to lower overall project costs. edu De-An Huang Robotics Institute [email protected] Introduction to Failure Analysis and Prevention Go Math Pacing Guide 5th Grade - 63pic. No matching sessions. 来了CMU，怎么能不选CS课程对吧~建议选修的CS院data相关课程： 10601/10701：Introduction to Machine Learning，10601是master级别的（偏码，老师是'郭美丽'，下面是Annamiss同学对这两门课的详细介绍：. edu) If you wish to email only the instructors, the email is [email protected] Smola and Barnabás Póczos; 10702: Statistical machine learning by Akshay Krishnamurthy and. Cmu 10701 fall 2018. View a sample email. CMU_10-701_Project. Hospital Affiliations Xavier University School of Medicine continuously works to build an assorted network of established hospitals and clinical institutions throughout the U. must register for bcmu 302 first; drop codes available in mkz 137. edu Michael K. How to give feedback • It should look like an actual conference review: • Summary of the paper/project • Some positive feedback about what is done well • Some constructive criticism about what needs to be improved. headwaters incorporated Headwaters is a leading manufacturer of building products for the residential construction, residential remodeling, commercial and institutional industries. Address City State ZIP; 308 East Bay Street: Nassau: 130 King Street West, Suite 2140: Toronto: 10745 Highway 119 South: Alabaster: AL: 35007: 83183 Highway 9: Ashland. 邢老师做事情还超级高标准， e5a48de588b67a6431333365643631 刚来CMU的第一年我先后修了他的10701机器学习和10708概率图模型（PGM）。他默认你课前都做完了课前的阅读和学习，每周还有一次作业，做出来时间因人而异，但是大体每次都是十页A4纸满满的latex打出来的公式. CMU v DARAB - Free download as Word Doc (. This course is designed to give a graduate-level student a thorough grounding in the methodologies, technologies, mathematics and algorithms currently needed by people who do research in machine learning, and related disciplines and applications. Popular Websites Part One - Free ebook download as (. del VALLE LA HISTORIA do so TAIlgo -U STO Y Nty U N A A 0 D E C I N E F I A N C E 5 OM V114111 AM NIAN PARIS enero, 1940. # 0x8e weights computed using reference implementation 1 0x8e 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0x8e 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0. CMU在阿德的校区非常小，不过一栋3层小楼其中约一半的空间。学生人数也不多，当时约150人，其中大半是21-month track的同学。 SCS还开设各类中高级机器学习课程，如10605 / 10701 / 10703等。. Cerfa 10701-01 Déclaration d'enrichissement des vins ; Cerfa 13602-02 Demande de subvention pour participer à un régime de qualité; Cerfa 87653-01 Formulaire d'inscription à la Démarche en ligne de déclaration d'ouverture de chantier. Introduction to Machine Learning CMU-10701 （以下简称Slides）之后得出的总结。记录下自己的成长。 目前写到LeNet部分，你的支持是我写下去的动力哦~ 大部分内容为英文直接翻译，一切版权归原作者Barnabás Póczos & Aarti Singh所有。. Use Trello to collaborate, communicate and coordinate on all of your projects. The nal course project will provide you the opportunity to explore such an application. 1BestCsharp blog 6,066,130 views. Thought I’d ask to confirm, though it looks bleak. Numerical Methods in Engineering CMU_24703. ijdwl a: dql (ind #73969, nsc # 732517 zl vxssol nci dctd. 1473219361100SUN STAR SERVICES LLC 400 WIMBERLEY OAKS DR WIMBERLEY TX78676-4675USA 512-618-5150 FWOAHAYS Construction management services. rtf - Free ebook download as (. Pradeep Ravikumar and Prof. This feature is not available right now. So to summarize, what I'd say is: CMU is the better school for ML/NLP and MIIS is a great program for it. single-family home is a 3 bed, 1. 86-631 Neural Data Analysis: 12 units (Cross listed as 42-631) Instructor: Steve Chase; Date/Time: T/R 1:30 PM – 2:50 PM; Location: MI 130. Hi all, Here are the predicted due dates for the upcoming homework's and project-related stuff. Address City State ZIP; 308 East Bay Street: Nassau: 130 King Street West, Suite 2140: Toronto: 10745 Highway 119 South: Alabaster: AL: 35007: 83183 Highway 9: Ashland. features derived from Internet Movie Database, are we able to improve the recommendation quality?. 85 1042378004 134911 | May 5 1998 4. The price of 59 Chestnut St has increased $50,001 during that time. edu) School Of Computer Science, Carnegie Mellon University. edu) Xiongtao Ruan ([email protected] -DOMINGO, 29 DE MAYO DE 1949 A11O "I" Cr6nica Ha6nira lu'let a voluntafias 'del Un cocktail Dispensario, San Lorenzo Almuerzo a Nenita del Couatio yi pre,. Yu Zhou (MS at CMU), Fall 2012 - Spring 2014. Course: Title: Units: Lec/Sec: Days: Begin: End: Bldg/Room: Location: Instructor(s) Machine Learning : 10301: Introduction to Machine Learning (Undergrad) 12. Broadway #312 Yonkers, NY 10701- tel. Deep Learning Workshop CMU http://www. to lower overall project costs. 2 Contents Motivation PCA algorithms Applications Some of these slides are taken from. Brooklyn, NY 11222 tel. This is an unofficial and probably incomplete fleet list for Stagecoach in Hastings. RS refers to the sections from the online draft of Computer Vision: Algorithm and Applications by Richard Szeliski. Carnegie Mellon University. entry codes available from instructor june 1. It is based on readings of the New Testement from Bible. A!O CXVIII DIARIO DE LA MARINA. CMU-10701 8. Beautiful 2 Bedroom 2 Bathroom is a Yonkers Apartment located at Ravine Ave. (B) Two-layered fully connected network. This schedule is tentative and subject to change. 29 922513096 115934 | May 1 1998 1. 在CMU里存在着4门都属于Intro to Machine Learning的课，对应着各种level的学生，分别为：这学期新开的undergrad 10-401，master 10-601，PhD 10-701和10-715。 虽然10-701和10-715都是PhD level，但区别在于10-715是开设给在ML方向的PhD，而10-701是给研究方向不是ML的PhD，或者ML的master。. Julian, The changes to the text on CRC are a step down rather than up in clarity. E-mail: [email protected] 我个人对于CMU 10701 Spring 2011课程的笔记。课程网址为https. del VALLE LA HISTORIA do so TAIlgo -U STO Y Nty U N A A 0 D E C I N E F I A N C E 5 OM V114111 AM NIAN PARIS enero, 1940. edu12 13 Abstract14. Introduction to Machine Learning CMU-10701 （以下简称Slides）之后得出的总结。记录下自己的成长。 目前写到LeNet部分，你的支持是我写下去的动力哦~ 大部分内容为英文直接翻译，一切版权归原作者Barnabás Póczos & Aarti Singh所有。. Recent CMU alum here ('15). Thanks to the marvels of modern technology, you can see where a particular vehicle has been recently, and which vehicles have operated a particular service. Time and Location: Monday, Wednesday 1:30 - 2:50pm, GHC 4401 Rashid Auditorium Class Videos: Class videos will be available here. { {AffiliationName}}. The property features a 2 BR rental unit available starting at$2000. docx Author: Administrator Created Date: 1/30/2018 11:13:51 AM. Phomaketide A Inhibits Lymphangiogenesis in Human Lymphatic Endothelial Cells. Fantasy, stage, drag or Halloween looks, brought to life by a highly skilled M·A·C Artist in 90 minutes. web; books; video; audio; software; images; Toggle navigation. CMU 10701 Spring 2011笔记. Mazda reserves the right to change product specifications at any time without incurring obligations. (10401 or 10601 or 10701 or 10715) any of these courses must be satisfied to take the course. Skip to content 10701 诚聘辅导. I would recommend 601 for most students to develop a functioning high-level understanding of machine learning sufficient for most practical applications, but 701 to develop strong foundations if you intend to go on to further graduate level ML studies. Time and Location: Monday and Wednesday, 10:30-11:50 (GHC 4307). CS345a:(Data(Mining(Jure(Leskovec(and(Anand(Rajaraman(Stanford(University(Clustering Algorithms Given&asetof&datapoints,&group&them&into&a. Click here to see all sessions. Find your yodel. FP refers to sections from Forsyth and Ponce (second edition). 10701 10701 10701 Item Specifications Whether you’re creating a street scene, castle, or something of your own imagination, this gray-colored 48x48-stud baseplate is the perfect starting point for building, displaying, and playing with your LEGO® creations. ) Instructor: Eric Xing; Location: Wean Hall 7500. edu/~aarti/Class/10701_Spring14/slides/DeepLearning. 2017-09-29 在CMU读Tepper商学院是怎样一种体验 2016-12-10 在CMU学习10701 Machine learning是种 2017-11-03 在CMU学习15319/619 Cloud Computin. For generic CMU questions, please use the. Deep Learning Essentials. Click the Bookmarks tab when you're watching a session. This Commercial is for sale on LoopNet. 11132 Cypress Leaf Drive Orlando FL 32825- (407) 381-7774 (407) 381-9855 434 Construction Corp. I took 10-701 and I know people who have taken 10-601 so here's what I think. Hi all, Here are the predicted due dates for the upcoming homework's and project-related stuff. Readbag users suggest that Chapter is worth reading. Box 678 Vestal NY 13851- (607) 770-1010 (607) 798-1898. CMU CSSA BBS. Introduction to Machine Learning (10-701) Fall 2017 Barnabás Póczos, Ziv Bar-Joseph School of Computer Science, Carnegie Mellon University Syllabus and (tentative) Course Schedule. 093013 Content updates. 【マークス公式】法人のお客さま専用BtoBサイトです。多彩なマークスの商品をオンライン上でご注文いただけます。カタログとしてもご利用いただけるほか、簡単に在庫の確認もできます。ダイアリー(8月下旬～出荷). pub; ce123 | 嵌入式软件开发; CodingCat | Coding Mechanics; Andrej Karpathy blog; Home - colah's blog; shenxiaolu1984的专栏 - CSDN; 中国人工智能学会; 机器学习资料. Discovery Of A Rossby Wave In Jupiter's South Equatorial Region. Machine Learning, 10-701 and 15-781, 2005. (Follow-up work of CMU-Cylab-10-006. in Computer Science. Carnegie Mellon University, Pittsburgh, PA 15213 {mbeckler, hongfeiw}@ece. rtf), PDF File (. It allows you and your students. Alok’s education is listed on their profile. 首先要来了解的一个概念就是聚类，简单地说就是把相似的东西分到一组，同Classification(分人工智能. >10701 b 1 th 1230-120 kne 130 0/ 20 cr/nc j first-year interest group >10722 a 2-6 f 130-320 cmu 243 frierson,dargan m 0/ 30e cr/nc credit/no credit add code required. Course: Title: Units: Lec/Sec: Days: Begin: End: Bldg/Room: Location: Instructor(s) Architecture : 48026: First Year Seminar: Architecture Edition II: 3. python (CMU 15112) Algorithms and advanced data structure (CMU 02613) Basic data analysis courses: INFSCI 2725 Data Analytics BIOST 2036 - INTRODUCTION TO HEALTH DATA SCIENCE INFSCI 2160 Data Mining INFSCI 2710 Database Management. A note to the instructor is a good way to do so. Machine Learning for Signal Processing 11755. Title: Microsoft Word - 外籍人士所得稅扣繳注意事項(10701-2). 来了CMU，怎么能不选CS课程对吧~建议选修的CS院data相关课程： 10601/10701：Introduction to Machine Learning，10601是master级别的（偏码，老师是'郭美丽'，下面是Annamiss同学对这两门课的详细介绍：. 91, Hsueh-Shih Road, Taichung, Taiwan. Would this credit be able to be used to fulfill my major. TEM characterization of Au/CeO 2-Al 2 O 3 showed well dispersed particles with an average Au crystalline size of 5-6 nm. View Alok Kothari’s profile on LinkedIn, the world's largest professional community. CMU深度学习课程资源! 教师：Bhiksha Raj（[email protected] -2013- My paper with Avinava Dubey, Sinead Williamson and Eric Xing on non-parametric topic modeling over time has been accepted in SIAM Datamining Conference 2013. CMU的Global MISM 项目第一学年 除了10601这个section，还有另外一个section——10701是郭美丽负责的，但课程load还是很重的样子，不仅会安排作业，还会有project，但有一说一，收获还是有很多的，如果让我重新选的话，我可能会 选择10701这个section。. The CeO 2-Al 2 O 3 support was prepared by co-precipitation. Through its coal combustion products, building products, and energy businesses, the Company earns a revenue stream that helps to provide the capital to fund growth of existing and new business opportunities. No matching sessions. It is based on readings of the New Testement from Bible. 0: A: TR: 01:30PM. CMU: Property Description. For example given these two objects a=[2, 2, 30, 4, 5], b=[2, 2, 30, 4, 5. Machine learning is about agents improving from data, knowledge, experience and interaction. CMU-10701 Markov Chain Monte Carlo Methods Barnabás Póczos & Aarti Singh. The last assessment recorded was taken in the year 2015 with a value of 6092877. Depends on what you want. View Notes - Lecture 18 from CMU 1070 at Carnegie Mellon University. Introduction to Machine Learning CMU-10701 Deep Learning Barnabás Póczos & Aarti Singh. CMU 10701 Spring 2011笔记. This banner text can have markup. Instructor: Nathan Urban; Location: Scaife 125; Days/Times: T/R 9:00AM to 10:20AM (Additional Lecture for Grad Students Thurs 4:30-5:50PM in MI 355). 邢老师做事情还超级高标准，刚来cmu的第一年我先后修了他的10701机器学习和10708概率图模型（pgm）。那真是我人生第一次感觉是："我知道这些都很有用，都很好，但是我真的不想学那么多啊呜呜呜呜呜呜". A repository for CMU 10701 Machine Learning project - hunterhector/ml-10701-project. Introduction to Machine Learning (PhD) Spring 2019, CMU 10701 Lectures: MW, 10:30-11:50pm, Rashid Autorium: 4401 Gates and Hillman Center (GHC) Recitations: F, 10:30-11:50pm, Rashid Autorium: 4401 Gates and Hillman Center (GHC). pdf Introduction to the term Deep Learning by this paper. CMU在阿德的校区非常小，不过一栋3层小楼其中约一半的空间。学生人数也不多，当时约150人，其中大半是21-month track的同学。因此大家非常熟悉，周末去学校有一种高三当年一起自习的感觉。学校的员工也非常亲切，很乐意在各方面协助学生。. AI là trí tuệ do con người lập trình với mục tiêu giúp máy tính có thể tự động hóa các hành vi thông minh như con người. me REPARE STEP FAQS - NIST GD Menu 2019 - General Denver Introduction to Machine Learning CMU-10701 PREMIER MINISTRE - Maison des eens. 11132 Cypress Leaf Drive Orlando FL 32825- (407) 381-7774 (407) 381-9855 434 Construction Corp. (10401 or 10601 or 10701 or 10715) any of these courses must be satisfied to take the course. この記事に対して1件のコメントがあります。コメントは「 Kernel Methods」です。. 2 Contents Decision Trees: Definition + Motivation Algorithm for Learning Decision Trees. The assigned Fed RSSD ID of Chase Bank is 852218. (Follow-up work of CMU-Cylab-10-006. Predicting Real-valued outputs. 1 Chemicals Gold (III) chloride trihydrate (HAuCl 4-3H 2 O) and chloroplatinic acid hexahydrate (H 2 PtCl 6-xH. 28 274974586 37119 | May 3 1998 4. ) Open Source Tool. Pelp;4Rivero 123 aiox al rervicio fie loi inte rea gencrales y peritianenei. Through its coal combustion products, building products, and energy businesses, the Company earns a revenue stream that helps to provide the capital to fund growth of existing and new business opportunities. 7, through 7. 邢老师做事情还超级高标准， e5a48de588b67a6431333365643631 刚来CMU的第一年我先后修了他的10701机器学习和10708概率图模型（PGM）。他默认你课前都做完了课前的阅读和学习，每周还有一次作业，做出来时间因人而异，但是大体每次都是十页A4纸满满的latex打出来的公式. Mazda reserves the right to change product specifications at any time without incurring obligations. Time and Location: Monday and Wednesday, 10:30-11:50 (GHC 4307). The property features a 2 BR rental unit available starting at $2000. 中國醫藥大學107 學年度 學生逕修讀博士學位申請表 申請系所： 老化醫學博士學位學程 申請日期： 年 月 日 就讀系所 學 號. Suggested relevant courses in MLD are 10701 Introduction to Machine Learning, 10807 Topics in Deep Learning, 10725 Convex Optimization, or online equivalent versions of these courses. You could not without help going when. 10701 線上開放式課程. Probability -- Lecture notes: http://www. Pittsburgh, PA 15213. Program Information. 中國醫藥大學磨課師線上開放式課程 CMU MOOCs; Nederlands (nl) Bahasa Melayu (ms) Deutsch (de) English (en) English (United States) (en_us) Español - Internacional (es) Español (México) (es_mx) Français (fr) Indonesian (id) Nederlands (nl) Português - Portugal (pt). Compare vehicles, and search car seat and tire ratings. It is also one of the first methods people get their hands dirty on. In the examples provided in Appendix B. Speaker recognition or broadly speech recognition has been an active area of re-search for the past two decades. Java Project Tutorial - Make Login and Register Form Step by Step Using NetBeans And MySQL Database - Duration: 3:43:32. Visit the course request form to get started. Once you begin participating in your courses you'll see this stream fill up with messages from discussions, grading updates, private messages between you and other users, etc. rtf), PDF File (. Introduction to Machine Learning CMU-10701 2. at [email protected] 助 教: 周昊（博士生），电院5号楼523，[email protected] This post is based on the assumption that the AdaBoost algorithm is similar to the M1 or SAMME implementations which can be sumarized as follows:. Julian, The changes to the text on CRC are a step down rather than up in clarity. Select a Benjamin Moore color to see how paint truly transforms a room. python (CMU 15112) Algorithms and advanced data structure (CMU 02613) Basic data analysis courses: INFSCI 2725 Data Analytics BIOST 2036 - INTRODUCTION TO HEALTH DATA SCIENCE INFSCI 2160 Data Mining INFSCI 2710 Database Management. pdf) or read book online for free. 106 線上開放式課程. ;2515;1;1;1;1;1 ---;Shell-Datenauszughandler;Zwischenspeicher;Win;2;1;1 ----;Datenauszugsobjekt;Zwischenspeicher;Win;3;1;1 mds;PX2;Top_Gun;Win;4;1;1 !bt;BitSpirit. View Notes - Lecture 2 from CMU 1070 at Carnegie Mellon University. Txt Large URL list. Ziv Bar-Joseph. Introduction to Machine Learning CMU-10701 Markov Chain Monte Carlo Methods Barnabás Póczos. Sparrow" tlegar -fti Obetan el decreto del Alcalde del Ejercito ea el Campo a La JIabana el dia 14 re n *as fah a de tiro de Pinar del Rio La Legacida Britinica en Cuba 0In0 IMI"ar Genera de. grade B or 05-610 Min. CMU一般指卡内基·梅隆大学. If you are on the waiting list, you have automatically subscribed to [email protected] Early detection of this form of defect can help to develop cost-effective rehabilitation methods for maintenance agencies. Through its coal combustion products, building products, and energy businesses, the Company earns a revenue stream that helps to provide the capital to fund growth of existing and new business opportunities. Principal Component Analysis Barnabás Póczos. 91, Hsueh-Shih Road, Taichung, Taiwan. Introduction to Machine Learning：这门课有两类课程，10601以及10701。 其中10601这门课程是Master课程，属于入学级别的课程，授课内容偏码 ，授课老师是郭教授，虽然不是资历很老的教授，但专业度还是很高的，而且也很认真负责。. edu De-An Huang Robotics Institute [email protected] 来了CMU，怎么能不选CS课程对吧~建议选修的CS院data相关课程： 10601/10701：Introduction to Machine Learning，10601是master级别的（偏码，老师是'郭美丽'，下面是Annamiss同学对这两门课的详细介绍：. Reading listed for each lecture is not mandatory unless otherwise specified. My CMU Andrew, Andy Blackboard, Blackboard Andrew CMU, Enhancing Education, Business/Finance Course Syllabus, Carnegie Mellon Blackboard, CMU Off-Campus Blackboard, Tepper Blackboard,. Using 10701-announce To post a message to all the list members, send email to [email protected] Course: Title: Units: Lec/Sec: Days: Begin: End: Bldg/Room: Location: Instructor(s) Machine Learning : 10301: Introduction to Machine Learning: 12. In general, 601 is broader, 701 is deeper. 【マークス公式】法人のお客さま専用BtoBサイトです。多彩なマークスの商品をオンライン上でご注文いただけます。カタログとしてもご利用いただけるほか、簡単に在庫の確認もできます。ダイアリー(8月下旬～出荷). Bookmarks will appear here. CMU Wilderness Multilingual Speech Dataset. Would this credit be able to be used to fulfill my major. Introduction to Machine Learning Documents. CMU 10701 Spring 2011笔记. Instructor: Nina Balcan Piazza Website: http://piazza. Scribd is the world's largest social reading and publishing site. 卡内基梅隆大学（Carnegie Mellon University），简称CMU，坐落在美国宾夕法尼亚州的匹兹堡(Pittsburgh)，研究型大学[1-2] 。该校拥有全美顶级计算机学院和戏剧学院，该校的艺术学院，商学院，工学院以及公共管理学院也都在全美名列前茅。. notice addendum no. Students as well as instructors can answer questions, fueling a healthy, collaborative discussion. 280 Chiang Mai J. edu Yurui Zhou Electrical & Computer Engineering [email protected] If you are on the waiting list, you have automatically subscribed to [email protected] pdf) or read book online for free. View Notes - Lecture 2 from CMU 1070 at Carnegie Mellon University. 2020; 47(2) 2. NASA Technical Reports Server (NTRS) Simon-Miller, Amy A. Machine Learning 10-702 (cross-listed as Statistics 36-702) Instructors: Ryan Tibshirani (ryantibs at stat dot cmu dot edu) Larry Wasserman (larry at stat dot cmu dot edu) TAs: Jisu Kim (jisuk1 at andrew at cmu at edu) Eric Lei (elei at cs dot cmu dot edu) Petar Stojanov (pstojano at cs dot cmu dot edu) Yining Wang (yiningwa at cs dot cmu dot edu). Mazda reserves the right to change product specifications at any time without incurring obligations. The CeO 2-Al 2 O 3 support was prepared by co-precipitation. 乘公交车到CMU和Pitt非常方便，也可步行至Pitt, CMU。附近环境安全安静，安全指标全绿。. Learn more about NameCoach. The HW due dates are not set in stone, but the other ones should be relatively reliable. (Follow-up work of CMU-Cylab-10-006. entry codes available from instructor june 1. Visit the course request form to get started. 11132 Cypress Leaf Drive Orlando FL 32825- (407) 381-7774 (407) 381-9855 434 Construction Corp. Please email Dr. Carnegie Mellon University, Pittsburgh, PA 15213 {mbeckler, hongfeiw}@ece. We get a lot of posts with very generic questions about majors, admissions, transfers, dorms, and so on. His principal research interests lie in the development of machine learning and statistical methodology; especially for solving problems involving. Carnegie Mellon University Master's degree Computer Science. Broadway #312 Yonkers, NY 10701- tel. More than 800 people took this test. Học bổng Chính phủ Trung Quốc (中国政府奖学金) có tên tiếng anh là Chinese Scholarship Council (CSC) là một chương trình học bổng được cung cấp bởi Bộ Giáo dục Trung Quốc để hỗ trợ sinh viên và các học giả từ khắp nơi trên thế giới đến học tập và nghiên cứu, tăng cường sự hiểu biết lẫn nhau và tình. edu) If you wish to email only the instructors, the email is [email protected] CMU的Global MISM 项目第一学年 除了10601这个section，还有另外一个section——10701是郭美丽负责的，但课程load还是很重的样子，不仅会安排作业，还会有project，但有一说一，收获还是有很多的，如果让我重新选的话，我可能会 选择10701这个section。. Data Structures. Announcements. Visit the course request form to get started. 91, Hsueh-Shih Road, Taichung, Taiwan. NameCoach is a tool that is integrated into Canvas and S3 and is designed to support inclusive teaching practices. Mazda reserves the right to change product specifications at any time without incurring obligations. Computer Networks. (B) Two-layered fully connected network. PRODUCT DESCRIPTION With Davis Colors, concrete products can be produced in a. Not all jobs at Google are equal. Instructor: Nathan Urban; Location: Scaife 125; Days/Times: T/R 9:00AM to 10:20AM (Additional Lecture for Grad Students Thurs 4:30-5:50PM in MI 355). edu Yurui Zhou Electrical & Computer Engineering [email protected] Decision Trees Barnabás Póczos. Applied Stochastic Processes SJTU. 抽象一点来讲，频率学派和贝叶斯学派对世界的认知有本质不同：频率学派认为世界是确定的，有一个本体，这个本体的真值是不变的，我们的目标就是要找到这个真值或真值所在的范围；而贝叶斯学派认为世界是不确定的，人们对世界先有一个预判，而后通过观测数据对这个预判. Title: Microsoft Word - 外籍人士所得稅扣繳注意事項(10701-2). 33/ 32 w concur registration in acctg 301 required. 36-401 Modern Regression. 2 Contents Markov Chain Monte Carlo Methods • Goal & Motivation Sampling • Rejection • Importance Markov Chains • Properties MCMC sampling • Hastings-Metropolis • Gibbs. Scribd is the world's largest social reading and publishing site. 首先要来了解的一个概念就是聚类，简单地说就是把相似的东西分到一组，同Classification(分人工智能. All books are in clear copy here, and all files are secure so don't worry about it. Keep following Piazza for any updates relevant to the course. Words - Free ebook download as Text File (. Parallel computing archtecture and programming 15618. -DOMINGO, 29 DE MAYO DE 1949 A11O "I" Cr6nica Ha6nira lu'let a voluntafias 'del Un cocktail Dispensario, San Lorenzo Almuerzo a Nenita del Couatio yi pre,. This 1,362 square foot multi-family home sits on a 1,306 square foot lot and features 3 bedrooms and 3 bathrooms. pdf), Text File (. Little Italy（lorigan st）现有house里多个单间即日起租。靠近UPMC Children Hospital, UPMC Shadyside Hospital, West Penn Hospital. Hi all, Here are the predicted due dates for the upcoming homework's and project-related stuff. So, is there any current or forthcoming support for egging from Maya 2012? Thanks!. [email protected] CMU深度学习课程资源！ 教师：Bhiksha Raj（[email protected] Carnegie Mellon University. 1 Chemicals Gold (III) chloride trihydrate (HAuCl 4-3H 2 O) and chloroplatinic acid hexahydrate (H 2 PtCl 6-xH. MATERIALS AND METHODS 2. 【マークス公式】法人のお客さま専用BtoBサイトです。多彩なマークスの商品をオンライン上でご注文いただけます。カタログとしてもご利用いただけるほか、簡単に在庫の確認もできます。ダイアリー(8月下旬～出荷). His principal research interests lie in the development of machine learning and statistical methodology; especially for solving problems involving. rtf - Free ebook download as (. edu Yurui Zhou Electrical & Computer Engineering [email protected] CMU [email protected] (The current archive is only available to the list members. python (CMU 15112) Algorithms and advanced data structure (CMU 02613) Basic data analysis courses: INFSCI 2725 Data Analytics BIOST 2036 - INTRODUCTION TO HEALTH DATA SCIENCE INFSCI 2160 Data Mining INFSCI 2710 Database Management. edu) Xiongtao Ruan ([email protected] { {AffiliationName}}. Machine Learning and Artificial Intelligence for Engineers CMU_24787. 2019 Apr 6;17(4). /usr/share/openvanilla/OVIMGeneric/uniliu. Assignment 3 Solutions Andrew Cmu Free Similar PDF's. Type a description and hit enter to create a bookmark. OpenJDK / jdk8 / jdk8 / nashorn changeset 414:edca88d3a03e Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression. Colored Concrete Block and Pavers PRODUCT NAME Davis Colors® Color Admixtures for Concrete Masonry Units (CMU), Concrete Pavers, and other colored concrete products. 11 ¡ Clustering in two dimensions looks easy ¡ Clustering small amounts of data looks easy ¡ And in most cases, looks are not deceiving ¡ Many applications involve not 2, but 10 or 10,000 dimensions ¡ High-dimensional spaces look different: Almost all pairs of points are very far from each other --> The Curse of Dimensionality! 1/22/20 Jure Leskovec, Stanford CS246: Mining Massive Datasets. Instructor: Nina Balcan Piazza Website: http://piazza. Description: The rate and amount of data being generated in today's world by both humans and machines are unprecedented. Box 678 Vestal NY 13851- (607) 770-1010 (607) 798-1898. Our goal is to remain current with the latest developments in the industry, adopt new technology, materials and processes, which will enable A. eu Sao Paulo 2014 April 4, 2014. Po wiecej informacji zapraszamy na nasza strone internetowa. 91, Hsueh-Shih Road, Taichung, Taiwan. in interesting books on Deep Learning Book Translation. CS345a:(Data(Mining(Jure(Leskovec(and(Anand(Rajaraman(Stanford(University(Clustering Algorithms Given&asetof&datapoints,&group&them&into&a. Deep Learning Essentials. E-mail: [email protected] Carnegie Mellon University, Pittsburgh, PA 15213 {mbeckler, hongfeiw}@ece. (The current archive is only available to the list members. Description. The Arivify. Program Information. 2 Contents Markov Chain Monte Carlo Methods Sampling • Rejection • Importance • Hastings-Metropolis • Gibbs Markov Chains • Properties Particle Filtering. | 10701: Machine Learning is a course taught at Carnegie Mellon University by. {"code":200,"message":"ok","data":{"html":". Skip to content 10701 诚聘辅导. May 04 2020 study-guide-and-reinforcement-teacher-edition 1/5 PDF Drive - Search and download PDF files for free. This multi-family home has been listed on Redfin since July 07, 2014 and is currently priced at$350,000. Instructor: Nathan Urban; Location: Scaife 125; Days/Times: T/R 9:00AM to 10:20AM (Additional Lecture for Grad Students Thurs 4:30-5:50PM in MI 355). View a sample email. 来了CMU，怎么能不选CS课程对吧~建议选修的CS院data相关课程： 10601/10701：Introduction to Machine Learning，10601是master级别的（偏码，老师是'郭美丽'，下面是Annamiss同学对这两门课的详细介绍：. I learned so much from them on how to be a good teacher. We saw the same spirit on the test we designed to assess people on Logistic Regression. CMU Wilderness Multilingual Speech Dataset. Basic Statistics Barnabs Pczos & Alex Smola Remember the color coding Important Not. 58 982952531 124324 | May 4 1998 4. However, if the prior probability in column 2 is changed, we may have a different answer. txt), PDF File (. Logistic Regression is likely the most commonly used algorithm for solving all classification problems. Data Structures. edu) x5527. This Commercial is for sale on LoopNet. The Rent Zestimate for this home is $1,799/mo, which has increased by$167/mo in the last 30 days. CMU-10701 14. in mathematical science and computer science Other Skills Expert knowledge of C ++. Time and Location: Monday and Wednesday, 10:30-11:50 (GHC 4307). This post is based on the assumption that the AdaBoost algorithm is similar to the M1 or SAMME implementations which can be sumarized as follows:. Time and Location: Monday and Wednesday, 10:30-11:50 (GHC 4307). This home was built in 1953 and last sold on 10/10/2017 for \$385,000. 4 - CRC Examples, the value is outlined as a word sent or received and therefore the CRC bits are mapped into the CRC word according to. Txt Large URL list. Click here to see all sessions. 在CMU里存在着4门都属于Intro to Machine Learning的课，对应着各种level的学生，分别为：这学期新开的undergrad 10-401，master 10-601，PhD 10-701和10-715。 虽然10-701和10-715都是PhD level，但区别在于10-715是开设给在ML方向的PhD，而10-701是给研究方向不是ML的PhD，或者ML的master。. CMU-10701 8. Lectures: Monday and Wednesday, 12:00PM to 1:20PM Location: Baker Hall A51 Recitations: Tuesdays 5:00PM to 6:00PM Location: Porter Hall 100 (January 22, 2013), Doherty Hall A302 (January 29, 2013 onwards). Title: Microsoft Word - 外籍人士所得稅扣繳注意事項(10701-2). CMU CSSA BBS. Joyce J Chosky, age 61, Traer, IA 50675 Background Check Known Locations: Yonkers NY 10701, Mamaroneck NY 10543 Possible Relatives: Jean B Chosky, Saul S Chosky. Click the Bookmarks tab when you're watching a session. This Commercial is for sale on LoopNet. Use the megathread to ask about CMU. The course will take a seminar format. Colored Concrete Block and Pavers PRODUCT NAME Davis Colors® Color Admixtures for Concrete Masonry Units (CMU), Concrete Pavers, and other colored concrete products. 武昌理工学院是经教育部批准设置的普通本科高校，前身是享有盛誉的武汉科技大学中南分校。经近20年发展，已成为一所以工学、管理学为主、多学科协调发展的知名高校。. It contains 0 bedroom and 1 bathroom. Introduction to Machine Learning CMU-10701 2. Session cookies are used in Mailman's private archive interface so that you don't need to re-authenticate with every operation. 为让我校学生进一步理解与掌握互联网、物联网、人工智能、云计算、大数据相关基础知识及实践技能，培养大学生的互联网思维与信息素养，更好地准备2020年度大学生创新创业训练计划项目及"互联网+"大学生创新创业大赛、计算机设计大赛、物联网设计竞赛、人工智能大赛等赛事，我中心决定. pdf), Text File (. Instructors: Sandra Kuhlman; Date/Time/Location: Tues & Thurs 9:00 AM – 10:20 AM (CMU Scaife Hall 125), Thurs 4:30 PM – 5:50 PM (Mellon Institute 355). 15 781 Machine Learning Recitation 1 By Jimeng Sun 9 15 05 Entropy Entropy Information Gain Decision Tree Probability Entropy Suppose X can have one … CMU CS 10701 - Recitation - GradeBuddy Cancel. Colored Concrete Block and Pavers PRODUCT NAME Davis Colors® Color Admixtures for Concrete Masonry Units (CMU), Concrete Pavers, and other colored concrete products. This is an unofficial and probably incomplete fleet list for Stagecoach in Hastings. Introduction to Machine Learning Documents. protocol update to calgb 10701/ctsu 10701 _____ a p hase ii s tudy of d asatinib (s prycel ®) (ind #73969, nsc #732517) as p rimary t herapy followed by t ransplantation for a dults ≥ 18 y ears with n ewly d iagnosed p h + a cute l ymphoblastic l eukemia by calgb, ecog and swog. I’ve been scouring the internet to see if there’s any support for maya2egg2012 to no avail. Readbag users suggest that Chapter is worth reading. E-mail: [email protected] Naval Air Station (NAS) Meridian is located in Meridian, Mississippi and serves as a key location for Navy tactical jet pilot training and produces fifty percent of the Navy's jet pilots via Training Air Wing One. Box 678 Vestal NY 13851- (607) 770-1010 (607) 798-1898. Speech Recognition and Understanding 11751. 10 701 15 781 Fall 2006 Midterm There are 7 questions in this exam 11 pages including this cover sheet Questions are not equally difficult If you nee… CMU CS 10701 - Midterm - GradeBuddy Cancel. The research described here received support from the National Science Foundation through Grants PHY-0757251 and PHY-1068331. Information Theory, Inference, and Learning Algorithms. Office of Human Resources. Use Trello to collaborate, communicate and coordinate on all of your projects. In fact, any class she teaches you should consider taking since she's probably the best lecturer Ive had at CMU (yes, beating Mackey and Von Ahn). Machine Learning for Signal Processing 11755. edu Laura Tipton7 8 Department of Computational 9 & Systems Biology 10 University of Pittsburgh 11 Pittsburgh, PA 15213 [email protected] Date: 2017-06-06. The department answers the need for professional skills and talents with an intense program that provides depth in fundamental mechanical engineering areas and breadth in emerging cross-boundary areas. 090913 Initial site update. Compare vehicles, and search car seat and tire ratings. Speaker:Jonathan Aldrich, Carnegie Mellon University, USA Abstract:Smart contracts running on blockchain platforms automate contracts between participants who have not established mutual trust. All books are in clear copy here, and all files are secure so don't worry about it. 10701: Machine learning by Alexander J. Discover more every day. edu/~aarti/Class/10701_Spring14/slides/DeepLearning. Stochastic Convergence Barnabás Póczos. Phone: 412-268-2565 Fax: 412-268-5576.


text:
# Decay Properties of $D$ and $D s$ mesons - High Energy Physics - Phenomenology

Decay Properties of $D$ and $D s$ mesons - High Energy Physics - Phenomenology - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Abstract: The decay rates and spectroscopy of the $D$ and $D s$ mesons are computed ina nonrelativistic phenomenological quark-antiquark potential of the type$Vr=-{4-3}\frac{\alpha s}{r}+A r^{ u}$ with different choices of $u$.Numerical method to solve the Schr\-odinger equation has been used to obtainthe spectroscopy of $q\bar{Q}$ mesons. The spin hyperfine, spin-orbit andtensor components of the one gluon exchange interactions are employed tocompute the spectroscopy of the excited $S$ states, low lying $P$-waves and$D$-waves. The numerically obtained radial solutions are employed to obtain thedecay constant and leptonic decay widths. It has been observed that predictionsof the spectroscopy and the decay widths are consistent with other modelpredictions as well as with the known experimental values.

Autor: Bhavin Patel, P C Vinodkumar

Fuente: https://arxiv.org/

DESCARGAR PDF

format: plain


text:
[This article was first published on rOpenSci - open tools for open science, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Last Thursday we held a Community Call discussing how to set up a Package to Foster a Community.

This call included speakers Maëlle Salmon, Hugo Gruson and Steffi LaZerte, and was moderated by Stefanie Butland.

## 🔗 Summarizing the community call

Scientific software development – and with that R packages – is a community effort. While there are often just a handful of developers maintaining an R package, the development really starts to thrive when users start to contribute.

In principle, every open source package has an open invitation to contribute. The question is how this invisible rule can be turned into something more explicit (and less intimidating) so that users who want to contribute can do so easily and feel welcomed and at ease. This brings us to the topic of rOpenSci’s last community call.

Over the course of an hour, the three speakers emphasised various aspects of an R package that can be used to invite code contributions, and to manage expectations of both users and contributors, for example through a contributor guide, or through explicit instructions how to use issues on GitHub. Speakers also emphasised the importance of the “soft skills” of package maintainers, especially the importance of considering the effect of how package maintainers interact with contributors, such as fostering opportunities to learn, being kind when saying “no”, and always acknowledging contributions.

### 🔗 Speakers

The three speakers were:

• Maëlle Salmon, a research software engineer, part-time with rOpenSci
• Hugo Gruson, a research software engineer and evolutionary biologist
• Steffi LaZerte, an R programming consultant, and part-time community assistant at rOpenSci

### 🔗 Maëlle Salmon: Community of a package (video)

A package has many different actors – the package authors, the users, the contributors – and they may act and interact with each other in a variety of ways.

Each role has slightly different needs. Everyone wants a better, well-maintained package. But the authors may want citations and grateful users, the users themselves may want certain features, and the contributors might seek recognition.

Also, authors may need help in tackling issues and who better to help than someone with a user perspective!

Before diving into tips, Maëlle talked about how authors can improve their communication with contributors. One of the best ways to encourage and retain contributors is simply being kind. But emojis can also be a great tool to compensate for lack of nuances, for example, when having to say “no”.

Maëlle then suggested three steps to foster a community for a package:

#### 🔗 1. Define rules & standards for your package

Some “rules & standards” include:

• Add a code of conduct: usethis::use_code_of_conduct()
• Add a citation to help people to cite your package: usethis::use_citation()
• Add a contribution guide: store as CONTRIBUTING.md, add style preferences, process preferences, scope lined out, how you prefer testing to work.

### 🔗 Hugo Gruson: Journey from user to contributor (video)

Hugo spelled out the obvious – that every package contributor is a) a user first and b) starts out as a beginner.

Hugo himself followed his favourite package where at one point he noticed something that needed fixing. So he fixed it – an intimidating process at first. But he repeated that, and after some time became an official maintainer.

Hugo’s talk focussed on how to facilitate the transition from user to contributor and suggested five tips for package maintainers to make contributing less scary:

#### 🔗 1. Have confidence in your project + expect contribution

(if you don’t, you may miss messages from users)

#### 🔗 2. Show that you are available and want to communicate

Use GitHub, Twitter, email for that. For example, tweet the NEWS file after a release.

#### 🔗 3. Don’t let contributors work for nothing / feel ignored

• Mention the name of the person.
• Keep them in the loop.
• Share a roadmap of project.

#### 🔗 4. Reduce workload for contributors

• Disable failing tests.
• Disable unimportant bots (Hugo mentioned the notoriously confusing coverage bot)

#### 🔗 5. Leave opportunities to learn

In GitHub, don’t abuse “allow edits from maintainers”, as this is demotivating (“Don’t take the keyboard from the learner”, Carpentry)

### 🔗 Steffi LaZerte: GitHub Issues as the low hanging fruits (video)

Steffi found the low-hanging fruits in making packages more contributor-friendly – GitHub issues!

GitHub issues can be labeled, and labels can be searched by users who want to become contributors but are maybe too shy to tackle an unlabelled issue.

So why not label some well-defined issues with "help wanted", a clear open invitation to users.

Other options for labeling include:

Because package maintainers rarely have time for this, the idea of a social label-athon – labeling issues in a social setting – was born and is happening for the first time on Thursday 29 April 2021 at 16:00 UTC (sign up).

At this Social, participants will get together on Zoom, have some time to meet and greet, and will then spend time co-working (working at the same time on different projects) to make their repositories more contributor-friendly.

The idea is to make this relatively low-priority task a bit more fun, and to offer a chance to socialize with others in the rOpenSci community.

## 🔗 Questions (video | document)

• (Athanasia Mo Mowinckel) How do you label issues you want help with that are really hard? (video | document)

• (Lluís Revilla Sancho) Are there examples/stories of “help wanted” labels on issues that were taken by users/external contributors? (video | document)

• (Kathryn Doering) Any tips for working with contributors that aren’t that comfortable with git/github? (video | document)

• (Silvia Canelón) Some packages ask contributors to sign a Contributor License Agreement (CLA) – when is this recommended/necessary? (video|document)

• (Rob Crystal-Ornelas) Many of the suggested files have standardized names, is this convention or does it enable features on GitHub? (document)

• (Athanasia Mo Mowinckel) Are there any best-practices in terms of formatting NEWS.md files? (document)

• (Silvia Canelón) What kind of positive response did Hugo notice after sharing NEWS.md on social media? (document)

• (Jeremy Selva) The easystats R package has this cool feature to classify issues. Any idea how to do this? (document)

• (Sina Rüeger) Maëlle, you mentioned badges for README, can you elaborate on that? (document)

• (Ella Kaye) In terms of encouraging users to contribute, do you have any advice on how to leverage twitter to get attention for it? (document)

• (Sina Rüeger) Now that there will be labelathons in co-working mode, could there be a time where some issues are tackled in co-working fashion, similar to a tidydev day? (document)

• (Wayne Smith) Is there a convention for where to put ORCID–readme.md? Citation? or? (document)

• (Valentina Costa) For a released package that is still a work in progress do you suggest immediately adding contributors to your contributor list? (document)

• (Janani Ravi) Is there a good way to indicate in contributing guidelines that contributions may result in co-authorship/acknowledgements in the subsequent publication? (document)


text:
Derived Reid's recipe for abelian subgroups of $SL^3$

Timothy Logvinenko
(Cardiff University)
Seminar
Wednesday, 11 September, 2013, at 16:30-17:30, in Aud. D3 (1531-215)
Abstract:

The classical McKay correspondence is a 1-1 correspondence between non-trivial irreducible representations of a finite subgroup $G$ of $SL^2(C)$ and irreducible divisors on the minimal resolution $Y$ of $C^2/G$.

In this talk I first introduce, explain and illustrate this classical correspondence. Then I describe joint work with Sabin Cautis and Alastair Craw in which we generalise it to dimension three using the famous Bridgeland-King-Reid derived equivalence. Specifically, we show a natural way to extract from this equivalence a correspondence between irreducible representations of $G \subset SL^3(C)$ and exceptional subvarieties of $Y = G-Hilb(C^3)$. The same method applied to $G \subset SL^2(C)$ produces the classical McKay.

Organised by: QGM
Contact person: Sergey Arkhipov


text:
# Chart Junk in the New York Times

Checking out the New York Times’s infographic on the housing bubble, I thought “wow! Look at how much prices climbed!”. Then I read the fine print and realized they’ve completely distorted the vertical scale to make the increase look enormous.

The Y-axis is the house price. 100=the 1987 price of a house, so if in 1992 the line of the graph is at 92 then a house that sold for $100,000 in 1987 sells for$92,000 in 1992. The problem is that it’s about an inch from $0 (the bottom of the graph) to$100,000. But then each inch on the Y-axis corresponds to about $10,000 in price gain. In effect, they’ve zoomed in on the area from 100-150 and magnified the growth in the last 15 years. I’m the first to say the housing market was overinflated and is now crashing—I took a bath when I sold my house in Colorado—but shame on the NYT for using misleading graphics to build its case. Perhaps they should invest in a copy of Darrell Huff’s magnificent How to Lie with Statistics—on page 62 this exact issue is illustrated and decried. tags: • kshep Similarly, when their intent last year was to show how much prices had risen, their graph set the “100” benchmark at 1890 and set the minimum Y value at 60. • rick gregory The graph is not only misleading but rather useless. No one buys a house in some mythical average town… we buy and sell houses in specific markets. Here in Seattle home prices are rising while in some markets they’re falling, in others cratering and in some they’re essentially flat. By averaging all of this diverse activity together the graphic *loses* information at the same time it distorts the point. Someone get that chart a beer, it’s working awfully hard. • http://btucker.org/blog Ben Tucker Not sure I’d characterize this as “distorting” the Y-axis. If they were “distorting” it the ’91 to ’99 region would appear nearly flat. I think the problem here is that the baseline is intended to be 100, not 0. But since they needed to show that it dropped below the baseline they raised it up off the bottom of the chart. Probably what they should have done is brought the X-axis labels up to the 100 baseline and then let the period from ’91 to ’99 overrun below it. • http://www.aleax.it Alex Martelli An excellent analysis and critique of the graph in question was just posted at the Calculated Risk blog. • http://tungwaiyip.info/ Wai Yip Tung The lowest point is at 92 in the end of 96. After 10 years of rally it climbs up to 160 at the beginning of 2007. That come to just about 5.7% gain per year. Not bad, but not spectacular. Besides this is the best performing 10 years. The previous 10 years is a bust with 0.8% annual lost. However, do notice the chart is already adjusted for inflation. • http://mistakengoal.com Kevin Guidry This is nothing new, either in general or for the NYT. I think it’s in Edward Tufte’s 1st edition of “The Visual Display of Quantitative Information” where he presents a figure from the NYT that similarly distorts the data and proceeds to define the “Lie Factor.” As defined by Tufte, the Lie Factor is equal to the size of the effect shown in the graphic divided by the size of the effect in the actual data. He asserts that a Lie Factor of between .95 and 1.05 is acceptable. Tufte’s book was published in the early 80s (82 or 83) and the original graphic he used was from the late 70s. Glad to see that times have not changed! • http://www.radar.com/nat nat Alex: thanks for the pointer, that’s a good piece. • http://www.jesselegg.com Jesse Legg You’ve misinterpreted. The bottom of the graph is not$0 but rather near $88,000 –$90,000. The scale is accurate, though they may have overestimated their readers’ ability to recognize it.

The Times often cuts off the bottom portion of charts like this. As well they should: the interesting part is the mountain top, everything below the lowest value is redundant.

• http://grandcanyonhiker.com Ken McNamara

Here’s a correctly scaled version of the graph:

People with an axe to grind have been messing with the sense of proportion since long before computers were helping them do it.

While I agree in general with the idea that statistics and charts can lie, and that this technique in particular can be used to selectively distort the data, I don’t find this graphic all that distortive. When you take a look at the full graphic as supplied by Ken Macnamara, you see just how big the run up has been as a percentage of the total house price. In some ways, the message is stronger than the one in the original graph with the bottom cut off.

• http://stevebosman.co.uk Steve Bosman

Even adjusted, the graph is still (potentially) misleading. Showing one bust then boom is not enough.

To be useful you need to be shown what happened prior to 1987, in particular was 1987 near the top of a long rise itself? This way you can determine whether to expect a large fall back close to pre-boom or a relatively small one (like the one shown in the 1990s).

• Sol

Another chart but frankly the conclusion remains the same and I dont agree at all with the original post about the chart @NYT.

• John Kuo

You didn’t note that the term ‘chartjunk’ was coined by Ed Tufte, who talks extensively about this phenomena in ‘The Visual Display of Quantitative Information.’

• http://www.arkansawyer.com/wordpress/ John A Arkansawyer

It wouldn’t’ve hurt the original piece to include a small copy of the graphic with the bottom intact, to give a little more context, but it’s not all that misleading.

More to the point, it’s not chartjunk. It may be a junky chart, but chartjunk it’s not.

• http://www.anshublog.com Anshu Sharma

For whatever reason, Google Finance plots all stock charts this way – which I find very very annoying. I think the (naive and wrong) argument is that you want to capture and zoom in on the part of the chart where there is most variation. Problem is, we loose all context and a share rising by 1% can look to have a better chart than a share that went up by 30%.

So – even the Google geniuses got it wrong. Why blame NY Times.

• Bil

Anshu, I think you have this backwards. Google’s way of showing stocks might result in a share gaining $1 looking like it outperformed a share gaining$30 (for example a $10 stock going to$11 vs a $500 going to$530), but not 1% vs 30%. And in fact, a $10 share gaining$1 is in fact outperforming the $500 share gaining$30.

As to the original post, it seems like you’re attributing malice to the NYT undeservedly. As Ken McNamara’s chart shows, there’s little to be gained from printing blank space (especially in a space limited environment like a newspaper page!).

• http://www.graphpaper.com Christopher Fahey

I agree with those who say this isn’t a bad chart. Ken McNamara’s remake of the chart demonstrates what’s happening in the diagram — but anyone who knows how to reach charts should have been able to do much of this visualization adjustment in their heads just by comparing the distance between the baseline and the 100 mark and comparing it to the rest of the chart. How anyone could think the baseline was *zero* is beyond me.

Really, Nat, did you think for even a second that the price of a house in America went up 1000% between 1995 and today? I think it’s reasonable for the New York Times to expect their audience to be both educated and to use their common sense when interpreting their stories and charts. Ken McNamara’s chart is, indeed, slightly more accurate… but to my eyes it’s also “dumbed down” and frankly wastes a lot of space.

This sort of chart *cropping* (not at all *distorting*) is a standard practice. It requires a certain degree of chart-reading literacy, I suppose, but this display method is so common I’m surprised that anyone doesn’t “get it” right away.

To those that say it’s a NYT deliberate distortion because the NYT has some sort of agenda, well, jeez, please take the tin foil hats off. Again, refer to Ken McNamara’s chart and it’s clear that this bubble is freaking insane. Housing prices doubled in a decade. The NYT should not be accused of deliberate distortion for noting that a 200% increase in one decade is pretty crazy.

Finally, the word “chartjunk” doesn’t simply mean that the chart is bad. It means that the chart contains useless and decorative elements that distract from the viewer’s ability to read the chart. This chart does not include any significant chartjunk.

• http://www.graphpaper.com Christopher Fahey

Also, to the tinfoil-hat wearers, please look at Sol’s link that shows this bubble is anomalous for the last *century*. If anything, I suppose we could just as well accuse the Times of hiding the degree of the bubble’s insanity, not exaggerating it.

• Arthur

NYTimes has been distorting facts since it was established. I thought you libertarians in the valley knew about this back since back in college at least.

• Arthur

And strictly speaking, this isn’t chart junk. “Chart junk” was coined to describe something else.

• http://www.arkansawyer.com/wordpress/ John A Arkansawyer

Consider what this graph would look like as a sparkline before you’re quick to condemn it.

• http://kingsley2.com Kingsley Joseph

Y’all seemed fine with it when Al Gore did it in his movie.

• Matthaeus Flexibilis

I’m with Mr. Fahey above. On the one hand, the chart does exaggerate, but on the other, it also shows more detail by omitting the part of the data that doesn’t change — we can see more of the dips and peaks than we could if the entire range were shown. It just expects a little more of the reader.

It reminds me of visiting Italy before the Euro: the number of Lira for modest items was ridiculously high (I think the exchange rate at the time was like 1500 Lira for \$1). They could have divided by a hundred or a thousand and not lost any information because the least significant price digits almost never changed.

If we were to plot the absolute prices of items in Lira, it would tend to obscure differences, but what we really cared about would look essentially like the NYT graph, which omits the superfluous zeros and shows the variations in greater detail.

PS, Don’t forget the old adage about “lies, damn lies, and statistics.”


text:
### Session T2: Defects and Strain in Graphene

2:30 PM–5:30 PM, Wednesday, March 23, 2011
Room: Ballroom A2

Chair: Brian LeRoy, University of Arizona

Abstract ID: BAPS.2011.MAR.T2.3

### Abstract: T2.00003 : Graphene under a tip

3:42 PM–4:18 PM

MathJax On | Off     Abstract

#### Author:

Eva Y. Andrei
(Department of Physics and Astronomy, Rutgers University, Piscataway NJ)

The strictly two dimensional structure of graphene results in 2D charge carriers that are readily accessible by surface probes such as scanning tunneling microscopy (STM) and spectroscopy (STS), and in electronic properties that can be controlled through doping, strain and external potentials. At the same time the 2D structure causes graphene to be extremely sensitive to environmental disturbances. I will describe STM, STS and magneto-transport experiments showing that when graphene is decoupled from substrate-induced potential fluctuations the intrinsic properties of the carriers become apparent. This is clearly seen in suspended graphene devices where, in the absence of substrate induced potential fluctuations, electron-electron interactions lead to a fractional quantum Hall effect and to an insulating phase at the Dirac point [1]. We find that even for non-suspended graphene it is possible to find non-invasive substrates on which one can directly observe the sequence of quantized Landau levels [2] and to track their evolution with field and doping down to the Dirac point where interaction effects kick in [3]. When the substrate'' is another graphene layer with relative orientation other than that of the standard Bernal stacking, it can profoundly affect the electronic density of states transforming it from the linear massless Dirac spectrum to one containing prominent Van Hove singularities which are controlled by the degree of twist between the layers [4].\\[4pt] [1] X. Du, I. Skachko, F. Duerr, A. Luican, EYAndrei, Nature \textbf{462}, 192 (2009)\\[0pt] [2] G. Li, A. Luican and E. Y. Andrei, Phys. Rev. Lett. 102, 176804 (2009).\\[0pt] [3] A. Luican, G. Li, and E. Y. Andrei, Phys Rev. B (R) (2011)\\[0pt] [4] G. Li, A. Luican and E. Y. Andrei, Nature Physics 6, 109 (2010)

To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2011.MAR.T2.3


text:
# PDE with constant coefficient using orthogonal transformation

1. Mar 27, 2006

### sara_math

Plz Help :(

Hi

I want 2 know how 2 solve 1st order partial differintial equation (PDE) with constant coefficient using orthogonal transformation

example :
solve: 2Ux + 2Uy + Uz = 0

THnx

2. Mar 27, 2006

### Tom Mattson

Staff Emeritus
I would tackle this one geometrcially. You can express the left side of your PDE in terms of a directional derivative, as follows:

$$D_{\vec{v}}u=0$$
$$\vec{v}\cdot\vec{\nabla}u=0$$

Now let me ask you something:

Can you identify $\vec{v}$? Can you figure out the lines along which $u$ is constant?

3. Mar 30, 2006

### sara_math

Thnx sir

but the dr. who teach me, didn't use this way with us

when we have aUx+bUy+cU=f , where a,b,c,f are constants
he take tan(r)=b/a
then he find r
after that take w=xcosr+ysinr , t=-xsinr+ycosr
then find Ux , Uy
that's it

can i take same w, t and z=z ???

4. Mar 30, 2006

### Tom Mattson

Staff Emeritus
My approach is not much different from your professor's.

This equation:

can be written in the following form.

$$D_{\vec{v}}u+cu=f$$

where $\vec{v}=<a,b>$.

What your instructor did was rotate the x-axis so that it coincides with the vector $\vec{v}$. In that coordinate system there is only one independent variable, and so you effectively have an ODE. The rotation matrix that carries $\{x,y\}$ into $\{w,t\}$ is given by the following.

$$R_{z}(r) = \left[\begin{array}{cc} \cos(r) & \sin(r)\\ -\sin(r) & \cos(r) \end{array}\right]$$

No, that's not it. All that does is transform the equation. It still remains to solve it.

You will want to do a rotation about some axis so that one coordinate axis is parallel to $\vec{v}=<a,b,c>$.

Last edited: Mar 30, 2006


text:
# Rearranging Limit Problem

Having some trouble expressing the following:

Find $\displaystyle \lim_{x\to\infty} \frac{2-3x+4x^2}{7 + 12x + 3x^2}$, by first expressing the limit as $\displaystyle \lim_{x\to0} f(x)$, for some real function $\displaystyle f$

My initial thoughts would be to switch the numerator and the denominator and then evaluate at $\displaystyle x\to0$, which would leave an answer of $\displaystyle \frac{7}{2}$, but this seems too easy and is thus more than likely incorrect.

-

First write $${2-3x+4x^2\over 7+12x+3x^2}= {{2\over x^2}-{3\over x}+4\over {7\over x^2}+{12\over x}+3}.$$ Then the limit is expressed by (setting $u=1/x$ in the above) $$\lim_{u\rightarrow0}{{{2u^2}-{3u}+4\over {7u^2}+{12u}+3}} .$$

-
Aha! Because 1/x tends to 0! So as x tends to infinity 1/x = u tends to 0, thanks David. –  Billy Ray Valentine Apr 10 '12 at 14:11
@BillyRayValentine You're welcome. (Ignore my last (deleted) comment). –  David Mitra Apr 10 '12 at 14:15
Changing variables is inefficient. Rather, simply employ the useful Principle of Domination to deduce the that limit of a quotient is the limit of the quotient of the "dominant" terms, namely factor out the dominant terms from each sum as follows (where limits are as $\rm\:x\to \infty)$ $$\rm\ \frac{f}g\to a,\ \ \frac{f_j}f \to 0,\ \ \frac{g_j}g \to 0\ \ \Rightarrow\ \ \frac{f + f_1 +\cdots f_n}{g + g_1\cdots g_k} \ =\ \frac{f}g\: {\frac{1 + \dfrac{f_1}f+\cdots+\dfrac{f_n}f}{1 + \dfrac{g_1}g +\cdots + \dfrac{g_k}g}}\:\!\to\: a$$
Therefore $\rm\ \ \dfrac{x}{x^2} = \dfrac{1}{x}\to 0,\ \ \dfrac{1}{x^2}\to 0\ \ \Rightarrow\ \ \dfrac{ax^2+bx+c}{dx^2+ex+f}\ =\ \dfrac{a + \dfrac{b}x + \dfrac{c}{x^2}}{d + \dfrac{e}x + \dfrac{f}{x^2}}\to\: \dfrac{a}d$


text:
# Diagonalizable matrix

(Redirected from Diagonalisable)

In linear algebra, a square matrix A is called diagonalizable if it is similar to a diagonal matrix, i.e., if there exists an invertible matrix P such that P−1AP is a diagonal matrix. If V is a finite-dimensional vector space, then a linear map T : VV is called diagonalizable if there exists an ordered basis of V with respect to which T is represented by a diagonal matrix. Diagonalization is the process of finding a corresponding diagonal matrix for a diagonalizable matrix or linear map.[1] A square matrix that is not diagonalizable is called defective.

Diagonalizable matrices and maps are of interest because diagonal matrices are especially easy to handle: their eigenvalues and eigenvectors are known, one can raise a diagonal matrix to a power by simply raising the diagonal entries to that same power, and the determinant of a diagonal matrix is simply the product of all entries. Geometrically, a diagonalizable matrix is an inhomogeneous dilation (or anisotropic scaling) — it scales the space, as does a homogeneous dilation, but by a different factor in each direction, determined by the scale factors on each axis (diagonal entries).

## Characterization

The fundamental fact about diagonalizable maps and matrices is expressed by the following:

• An n×n matrix A over the field F is diagonalizable if and only if the sum of the dimensions of its eigenspaces is equal to n, which is the case if and only if there exists a basis of Fn consisting of eigenvectors of A. If such a basis has been found, one can form the matrix P having these basis vectors as columns, and P−1AP will be a diagonal matrix. The diagonal entries of this matrix are the eigenvalues of A.
• A linear map T : VV is diagonalizable if and only if the sum of the dimensions of its eigenspaces is equal to dim(V), which is the case if and only if there exists a basis of V consisting of eigenvectors of T. With respect to such a basis, T will be represented by a diagonal matrix. The diagonal entries of this matrix are the eigenvalues of T.

Another characterization: A matrix or linear map is diagonalizable over the field F if and only if its minimal polynomial is a product of distinct linear factors over F. (Put in another way, a matrix is diagonalizable if and only if all of its elementary divisors are linear.)

The following sufficient (but not necessary) condition is often useful.

• An n×n matrix A is diagonalizable over the field F if it has n distinct eigenvalues in F, i.e. if its characteristic polynomial has n distinct roots in F; however, the converse may be false. Let us consider
${\displaystyle {\begin{bmatrix}-1&3&-1\\-3&5&-1\\-3&3&1\end{bmatrix}},}$
which has eigenvalues 1, 2, 2 (not all distinct) and is diagonalizable with diagonal form ( similar to A)
${\displaystyle {\begin{bmatrix}1&0&0\\0&2&0\\0&0&2\end{bmatrix}}}$
and change of basis matrix P
${\displaystyle {\begin{bmatrix}1&1&-1\\1&1&0\\1&0&3\end{bmatrix}}.}$
The converse fails when A has an eigenspace of dimension higher than 1. In this example, the eigenspace of A associated with the eigenvalue 2 has dimension 2.
• A linear map T : VV with n = dim(V) is diagonalizable if it has n distinct eigenvalues, i.e. if its characteristic polynomial has n distinct roots in F.

Let A be a matrix over F. If A is diagonalizable, then so is any power of it. Conversely, if A is invertible, F is algebraically closed, and An is diagonalizable for some n that is not an integer multiple of the characteristic of F, then A is diagonalizable. Proof: If An is diagonalizable, then A is annihilated by some polynomial ${\displaystyle (x^{n}-\lambda _{1})\cdots (x^{n}-\lambda _{k})}$, which has no multiple root (since ${\displaystyle \lambda _{j}\neq 0}$) and is divided by the minimal polynomial of A.

As a rule of thumb, over C almost every matrix is diagonalizable. More precisely: the set of complex n×n matrices that are not diagonalizable over C, considered as a subset of Cn×n, has Lebesgue measure zero. One can also say that the diagonalizable matrices form a dense subset with respect to the Zariski topology: the complement lies inside the set where the discriminant of the characteristic polynomial vanishes, which is a hypersurface. From that follows also density in the usual (strong) topology given by a norm. The same is not true over R.

The Jordan–Chevalley decomposition expresses an operator as the sum of its semisimple (i.e., diagonalizable) part and its nilpotent part. Hence, a matrix is diagonalizable if and only if its nilpotent part is zero. Put in another way, a matrix is diagonalizable if each block in its Jordan form has no nilpotent part; i.e., each "block" is a one-by-one matrix.

## Diagonalization

If a matrix A can be diagonalized, that is,

${\displaystyle P^{-1}AP={\begin{pmatrix}\lambda _{1}\\&\lambda _{2}\\&&\ddots \\&&&\lambda _{n}\end{pmatrix}},}$

then:

${\displaystyle AP=P{\begin{pmatrix}\lambda _{1}\\&\lambda _{2}\\&&\ddots \\&&&\lambda _{n}\end{pmatrix}}.}$

Writing P as a block matrix of its column vectors ${\displaystyle {\vec {\alpha }}_{i}}$

${\displaystyle P={\begin{pmatrix}{\vec {\alpha }}_{1}&{\vec {\alpha }}_{2}&\cdots &{\vec {\alpha }}_{n}\end{pmatrix}},}$

the above equation can be rewritten as

${\displaystyle A{\vec {\alpha }}_{i}=\lambda _{i}{\vec {\alpha }}_{i}\qquad (i=1,2,\cdots ,n).}$

So the column vectors of P are right eigenvectors of A, and the corresponding diagonal entry is the corresponding eigenvalue. The invertibility of P also suggests that the eigenvectors are linearly independent and form a basis of Fn. This is the necessary and sufficient condition for diagonalizability and the canonical approach of diagonalization. The row vectors of P−1 are the left eigenvectors of A.

When the matrix A is a Hermitian matrix (resp. symmetric matrix), eigenvectors of A can be chosen to form an orthonormal basis of Cn (resp. Rn). Under such circumstance P will be a unitary matrix (resp. orthogonal matrix) and P−1 equals the conjugate transpose (resp. transpose) of P.

In practice, matrices are diagonalized numerically using computers. Many algorithms exist to accomplish this.

## Simultaneous diagonalization

A set of matrices is said to be simultaneously diagonalizable if there exists a single invertible matrix P such that P−1AP is a diagonal matrix for every A in the set. The following theorem characterises simultaneously diagonalisable matrices: A set of diagonalizable matrices commutes if and only if the set is simultaneously diagonalisable.[2]

The set of all n×n diagonalisable matrices (over C) with n > 1 is not simultaneously diagonalisable. For instance, the matrices

${\displaystyle {\begin{bmatrix}1&0\\0&0\end{bmatrix}}\quad {\text{and}}\quad {\begin{bmatrix}1&1\\0&0\end{bmatrix}}}$

are diagonalizable but not simultaneously diagonalizable because they do not commute.

A set consists of commuting normal matrices if and only if it is simultaneously diagonalisable by a unitary matrix; that is, there exists a unitary matrix U such that U*AU is diagonal for every A in the set.

In the language of Lie theory, a set of simultaneously diagonalisable matrices generate a toral Lie algebra.

## Examples

### Diagonalizable matrices

• Involutions are diagonalizable over the reals (and indeed any field of characteristic not 2), with ±1 on the diagonal.
• Finite order endomorphisms are diagonalisable over C (or any algebraically closed field where the characteristic of the field does not divide the order of the endomorphism) with roots of unity on the diagonal. This follows since the minimal polynomial is separable, because the roots of unity are distinct.
• Projections are diagonalizable, with 0s and 1s on the diagonal.
• Real symmetric matrices are diagonalizable by orthogonal matrices; i.e., given a real symmetric matrix A, QTAQ is diagonal for some orthogonal matrix Q. More generally, matrices are diagonalizable by unitary matrices if and only if they are normal. In the case of the real symmetric matrix, we see that A = AT, so clearly AAT = ATA holds. Examples of normal matrices are real symmetric (or skew-symmetric) matrices (e.g. covariance matrices) and Hermitian matrices (or skew-Hermitian matrices). See spectral theorems for generalizations to infinite-dimensional vector spaces.

### Matrices that are not diagonalizable

In general, a rotation matrix is not diagonalizable over the reals, but all rotation matrices are diagonalizable over the complex field. Even if a matrix is not diagonalizable, it is always possible to "do the best one can", and find a matrix with the same properties consisting of eigenvalues on the leading diagonal, and either ones or zeroes on the superdiagonal - known as Jordan normal form.

Some matrices are not diagonalizable over any field, most notably nonzero nilpotent matrices. This happens more generally if the algebraic and geometric multiplicities of an eigenvalue do not coincide. For instance, consider

${\displaystyle C={\begin{bmatrix}0&1\\0&0\end{bmatrix}}.}$

This matrix is not diagonalizable: there is no matrix U such that U−1CU is a diagonal matrix. Indeed, C has one eigenvalue (namely zero) and this eigenvalue has algebraic multiplicity 2 and geometric multiplicity 1.

Some real matrices are not diagonalizable over the reals. Consider for instance the matrix

${\displaystyle B={\begin{bmatrix}0&1\\-1&0\end{bmatrix}}.}$

The matrix B does not have any real eigenvalues, so there is no real matrix Q such that Q−1BQ is a diagonal matrix. However, we can diagonalize B if we allow complex numbers. Indeed, if we take

${\displaystyle Q={\begin{bmatrix}1&{\textrm {i}}\\{\textrm {i}}&1\end{bmatrix}},}$

then Q−1BQ is diagonal.

Note that the above examples show that the sum of diagonalizable matrices need not be diagonalizable.

### How to diagonalize a matrix

Consider a matrix

${\displaystyle A={\begin{bmatrix}1&2&0\\0&3&0\\2&-4&2\end{bmatrix}}.}$

This matrix has eigenvalues

${\displaystyle \lambda _{1}=3,\quad \lambda _{2}=2,\quad \lambda _{3}=1.}$

A is a 3×3 matrix with 3 different eigenvalues; therefore, it is diagonalizable. Note that if there are exactly n distinct eigenvalues in an n×n matrix then this matrix is diagonalizable.

These eigenvalues are the values that will appear in the diagonalized form of matrix A, so by finding the eigenvalues of A we have diagonalized it. We could stop here, but it is a good check to use the eigenvectors to diagonalize A.

The eigenvectors of A are

${\displaystyle v_{1}={\begin{bmatrix}-1\\-1\\2\end{bmatrix}},\quad v_{2}={\begin{bmatrix}0\\0\\1\end{bmatrix}},\quad v_{3}={\begin{bmatrix}-1\\0\\2\end{bmatrix}}.}$

One can easily check that ${\displaystyle Av_{k}=\lambda _{k}v_{k}.}$

Now, let P be the matrix with these eigenvectors as its columns:

${\displaystyle P={\begin{bmatrix}-1&0&-1\\-1&0&0\\2&1&2\end{bmatrix}}.}$

Note that there is no preferred order of the eigenvectors in P; changing the order of the eigenvectors in P just changes the order of the eigenvalues in the diagonalized form of A.[3]

Then P diagonalizes A, as a simple computation confirms, having calculated P −1 using any suitable method:

${\displaystyle P^{-1}AP={\begin{bmatrix}0&-1&0\\2&0&1\\-1&1&0\end{bmatrix}}{\begin{bmatrix}1&2&0\\0&3&0\\2&-4&2\end{bmatrix}}{\begin{bmatrix}-1&0&-1\\-1&0&0\\2&1&2\end{bmatrix}}={\begin{bmatrix}3&0&0\\0&2&0\\0&0&1\end{bmatrix}}.}$

In fact, this follows abstractly from the fact that for the standard basis ${\displaystyle e_{1},e_{2},e_{3}}$ we have

${\displaystyle P^{-1}APe_{k}=P^{-1}Av_{k}=P^{-1}\lambda _{k}v_{k}=\lambda _{k}e_{k}.}$

where we make use of the fact that ${\displaystyle Pe_{k}=v_{k}}$ is the k-th column of ${\displaystyle P}$ and hence ${\displaystyle P^{-1}v_{k}=e_{k}}$. Note that the eigenvalues ${\displaystyle \lambda _{k}}$ appear in the diagonal matrix.

## An application

Diagonalization can be used to compute the powers of a matrix A efficiently, provided the matrix is diagonalizable. Suppose we have found that

${\displaystyle P^{-1}AP=D\Rightarrow PP^{-1}APP^{-1}=PDP^{-1}\Rightarrow A=PDP^{-1}}$

where ${\displaystyle D}$ is a diagonal matrix. Then, as the matrix product is associative,

{\displaystyle {\begin{aligned}A^{k}&=(PDP^{-1})^{k}=(PDP^{-1})\cdot (PDP^{-1})\cdots (PDP^{-1})\\&=PD(P^{-1}P)D(P^{-1}P)\cdots (P^{-1}P)DP^{-1}\\&=PD^{k}P^{-1}\end{aligned}}}

and the latter is easy to calculate since it only involves the powers of a diagonal matrix. This approach can be generalized to matrix exponential and other matrix functions since they can be defined as power series.

This is particularly useful in finding closed form expressions for terms of linear recursive sequences, such as the Fibonacci numbers.

### Particular application

For example, consider the following matrix:

${\displaystyle M={\begin{bmatrix}a&b-a\\0&b\end{bmatrix}}.}$

Calculating the various powers of M reveals a surprising pattern:

${\displaystyle M^{2}={\begin{bmatrix}a^{2}&b^{2}-a^{2}\\0&b^{2}\end{bmatrix}},\quad M^{3}={\begin{bmatrix}a^{3}&b^{3}-a^{3}\\0&b^{3}\end{bmatrix}},\quad M^{4}={\begin{bmatrix}a^{4}&b^{4}-a^{4}\\0&b^{4}\end{bmatrix}},\quad \ldots }$

The above phenomenon can be explained by diagonalizing M. To accomplish this, we need a basis of R2 consisting of eigenvectors of M. One such eigenvector basis is given by

${\displaystyle \mathbf {u} ={\begin{bmatrix}1\\0\end{bmatrix}}=\mathbf {e} _{1},\quad \mathbf {v} ={\begin{bmatrix}1\\1\end{bmatrix}}=\mathbf {e} _{1}+\mathbf {e} _{2},}$

where ei denotes the standard basis of Rn. The reverse change of basis is given by

${\displaystyle \mathbf {e} _{1}=\mathbf {u} ,\qquad \mathbf {e} _{2}=\mathbf {v} -\mathbf {u} .}$

Straightforward calculations show that

${\displaystyle M\mathbf {u} =a\mathbf {u} ,\qquad M\mathbf {v} =b\mathbf {v} .}$

Thus, a and b are the eigenvalues corresponding to u and v, respectively. By linearity of matrix multiplication, we have that

${\displaystyle M^{n}\mathbf {u} =a^{n}\,\mathbf {u} ,\qquad M^{n}\mathbf {v} =b^{n}\,\mathbf {v} .}$

Switching back to the standard basis, we have

${\displaystyle M^{n}\mathbf {e} _{1}=M^{n}\mathbf {u} =a^{n}\mathbf {e} _{1},}$
${\displaystyle M^{n}\mathbf {e} _{2}=M^{n}(\mathbf {v} -\mathbf {u} )=b^{n}\mathbf {v} -a^{n}\mathbf {u} =(b^{n}-a^{n})\mathbf {e} _{1}+b^{n}\mathbf {e} _{2}.}$

The preceding relations, expressed in matrix form, are

${\displaystyle M^{n}={\begin{bmatrix}a^{n}&b^{n}-a^{n}\\0&b^{n}\end{bmatrix}},}$

thereby explaining the above phenomenon.

## Quantum mechanical application

In quantum mechanical and quantum chemical computations matrix diagonalization is one of the most frequently applied numerical processes. The basic reason is that the time-independent Schrödinger equation is an eigenvalue equation, albeit in most of the physical situations on an infinite dimensional space (a Hilbert space). A very common approximation is to truncate Hilbert space to finite dimension, after which the Schrödinger equation can be formulated as an eigenvalue problem of a real symmetric, or complex Hermitian, matrix. Formally this approximation is founded on the variational principle, valid for Hamiltonians that are bounded from below. But also first-order perturbation theory for degenerate states leads to a matrix eigenvalue problem.


text:
# Finding the original matrix A from a given set of Eigenvalues and Eigenvectors

Say you're given a set of eigenvalues and eigenvectors, is it always possible to determine the original matrix A?

I recognize that if a matrix A is diagonalizable, the geometric multiplicity equals the algebraic multiplicity and you can form you matrix of Eigenvectors, call it Q, and then your diagonal matrix D (which consists of the eigenvalues that correspond to the correct eigenvector column in Q) gives you the result

$A = QDQ^-1$

but assuming we aren't given the original matrix A, is it possible to "reverse" this process and find A? Thanks

Assuming $A$ is $n\times n$, if you are given $n$ linear independent eigenvectors and the corresponding eigenvalues, then the $QDQ^{-1}$ formulation works.
If the matrix does not have this spanning set of eigenvectors, then you need the generalized eigenvectors, c.f. https://en.wikipedia.org/wiki/Generalized_eigenvector, to construct a matrix $P$ and the almost diagonal Jordan normal form $J$ such that $A=PJP^{-1}$.
Jordan normal forms, c.f. https://en.wikipedia.org/wiki/Jordan_normal_form, exist for all $n\times n$ matrices over the field $\mathbb{C}$, so the answer is "yes" if you are also given generalized eigenvectors and "no" if you are only given the eigenvectors of a non-diagonalizable matrix.


text:
# Calcium metal (Ca) can be produced by passing an electric current through molten calcium chloride (CaCl_2). Chlorine gas (Cl_2) is also formed. What is the balanced equation for this reaction?

$C a C {l}_{2} \left(l\right) + \Delta \rightarrow C a \left(l\right) + C {l}_{2} \left(g\right)$
If either quantity was unbalanced, we could not accept the equation as a legitimate representation of reality. What does the $\Delta$ symbol represent? Is this a redox reaction?


text:
# How many pyramids in a cube?

Knowing that a pyramid volume is computed as 1/3 of base multiplied by the height, how many pyramids may be constructed by connecting the corners of a cube to create pyramids with volume 1/3 of the cube volume?

Using a computer an exhaustive search of 4 out of 8 and 5 out of 8 could produce the result, but than it is not interesting, so explanation is expected.

I think,

26 pyramids

Method:

Consider a cube with side length $$1$$. Suppose that one of the sides of a pyramid coincides with a side of the cube. Fix that side as the base. Then picking the other vertex remaining as the apex (if one is remaining) would give volume zero, and picking one on opposite side would give the volume $$\frac{1}{3}$$ times the area of the base as the height is $$1$$. For this to be $$\frac{1}{3}$$ the base area must be $$1$$ which is only possible when we pick the whole side.
There are $$24$$ pyramids satisfying the above as there are $$6$$ possible bases and $$4$$ possible apices for each base.
Now consider all pyramids with an edge of length $$1$$. Note that for such a pyramid to not fall in the already considered category, the only possible vertices for that pyramid is the diagonally opposite pair to the already chosen pair. But choosing that gives a rectangle with volume zero, so there are no possibilities here.
Now consider all pyramids with an edge of length $$\sqrt{3}$$. But whatever vertex we pick next, the pyramid would have an edge of length $$1$$, so no possibilities here either.
So the only possibility remaining is the tetrahedron with all edges $$\sqrt{2}$$. Using the tetrahedron volume formula we see that this gives the required $$\frac{1}{3}$$ volume. Note that $$2$$ of those exists on the cube, as picking one edge uniquely determines all the other edges and there are $$6$$ edges to the tetrahedron compared to $$12$$ possible $$\sqrt{2}$$ edges, giving a total of $$26$$ pyramids.

• You select a diagonal. How many per edge?
– Moti
Sep 1 '19 at 14:53
• @Moti Can you please clarify more? :) Are you asking for each edge how many pyramids contain that edge?
– user47134
Sep 1 '19 at 15:07
• The answer 2 for the tetrahedron is not sure. A corner has 3 diagonals connected to it - each creates one, and all different since they have at least one diagonal that is not participating in other tetrahedron. Given 12 diagonals, how many selections of 2 out of 12 possible? How many 6 out of 12?
– Moti
Sep 1 '19 at 15:21
• I'm not trying to consider the tetrahedrons as a group in the solution. I'm only considering the regular tetrahedron: all other tetrahedrons fall under one of the categories I considered possibilities with. Also even though your argument is right, volume 1/3 condition eliminates most of them. I'm sorry if I'm misunderstanding though.
– user47134
Sep 1 '19 at 15:32
• If you are referring to the regular tetrahedron, a corner does not create 3 different of those, only one, because a tetrahedron on one diagonal includes the other two too. (Try drawing a cube and checking if this is not clear)
– user47134
Sep 1 '19 at 15:40

5 points:

Pyramids with 5 vertices are square pyramids. The base of the pyramid must obviously be one of the faces of the cube, and the apex of the pyramid can be any one of the 4 vertices in the opposite face of the cube. This means there are $$6*4=24$$ such pyramids.

4 points:

Pyramids with 4 vertices are triangular pyramids, i.e. tetrahedra. If three of the vertices lie in the same face of cube, then the pyramid's triangular face is half the cube's square face. For its volume to be $$1/3$$rd of the cube, its height would then have to be twice the height of the cube, so it is not possible for the apex to be another vertex of the cube.
So no three vertices of the pyramid can be in the same face. This leaves only two ways to choose four cube vertices:
a) The endpoints of two opposite edges of the cube. These lie in the same plane so do not form a tetrahedron.
b) A set of four non-adjacent vertices. There are two such sets. These form a regular tetrahedron with edge length $$\sqrt{2}$$ assuming the cube is a unit cube. The volume of this tetrahedron is $$\frac{a^3}{6\sqrt{2}}=\frac{2\sqrt{2}}{6\sqrt{2}}=\frac{1}{3}$$.

The total number of such pyramids is therefore:

$$24+2=26$$

• You select a diagonal. How many per edge?
– Moti
Sep 1 '19 at 14:54
• @Moti: I have no idea what you mean. Sep 1 '19 at 15:19
• My mistake. I mean per corner, not edge.
– Moti
Sep 1 '19 at 15:22