Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Analysis of boosting algorithms using the smooth margin function
Boosting as a Regularized Path to a Maximum Margin Classifier
On the importance of accurate weak classifier learning for boosted weak classifiers
Regularized Boost for Semi-Supervised Learning
MadaBoost: A Modification of AdaBoost
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
Query Learning with Large Margin Classifiers
Multi-class cost-sensitive boosting with p-norm loss functions
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation
Self Supervised Boosting
Revisiting AdaBoost for Cost-Sensitive Classification. Part II: Empirical Analysis.
Computational Complexity of Linear Large Margin Classification With Ramp Loss
Greedy Function Approximation: A Gradient Boosting Machine
Progressive Boosting for Class Imbalance
Improving Performance in Neural Networks Using a Boosting Algorithm
RAMOBoost: Ranked Minority Oversampling in Boosting
Automatic Gradient Boosting
Improvements to the SMO algorithm for SVM regression
An Efficient Boosting Algorithm for Combining Preferences
Boosting SVM classifiers by ensemble
Bagging, Boosting, and C4.5
Boosting Algorithms as Gradient Descent
Rigid-flexible coupling dynamics analysis of a spot-welding robot
A G-Band (140–220 GHz) planar stubbed branch-line balun in BCB technology
Circuit and Layout Co-Design for ESD Protection in Bipolar-CMOS-DMOS (BCD) High-Voltage Process
Understanding the Factors Driving NFC-Enabled Mobile Payment Adoption: an Empirical Investigation.