Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Optimal principal component analysis in distributed and streaming models
Numerical linear algebra in the streaming model
Adaptive filters for continuous queries over distributed data streams
Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors
A Comparative Study of Distributed Tools for Analyzing Streaming Data
A partially parallel splitting method for multiple-block separable convex programming with applications to robust PCA
Robust Distributed Linear Programming
State-of-the-art on clustering data streams
Dynamic Load Balancing for Ordered Data-Parallel Regions in Distributed Streaming Systems
Partial Key Grouping: Load-Balanced Partitioning of Distributed Streams
Dimension Reduction by Local Principal Component Analysis
Broadcast-based distributed alternating direction method of multipliers
A Tutorial on Principal Component Analysis with the Accord.NET Framework
New Routes from Minimal Approximation Error to Principal Components
Large-Scale Online Expectation Maximization with Spark Streaming
Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
Federated Optimization:Distributed Optimization Beyond the Datacenter
Sparse PCA via Bipartite Matchings
Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning
Sparse Communication for Distributed Gradient Descent
Optimal Distributed Online Prediction
Event cube: another perspective on business processes
BYTEWEIGHT: learning to recognize functions in binary code
Thoughtful Machine Learning - A Test-Driven Approach
Quality Signals in Generated Stories
Improved Approximation Algorithms for Large Matrices via Random Projections