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Distributed Learning

1100 directly classified papers

Papers per year

Papers

GURLS: A Least Squares Library for Supervised Learning JMLR 2013
Communication-Efficient Algorithms for Statistical Optimization JMLR 2013
Distributed and Adaptive Darting Monte Carlo through Regenerations AISTATS 2013
Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods AISTATS 2013
Divide and Conquer Kernel Ridge Regression COLT 2013
Deep learning with COTS HPC systems ICML 2013
Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training ICML 2013
Distributed training of Large-scale Logistic models ICML 2013
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models ICML 2013
Gossip-based distributed stochastic bandit algorithms ICML 2013
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server NIPS 2013
Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent NIPS 2013
Information-theoretic lower bounds for distributed statistical estimation with communication constraints NIPS 2013
Optimistic Concurrency Control for Distributed Unsupervised Learning NIPS 2013
Distributed $k$-means and $k$-median Clustering on General Topologies NIPS 2013
Distributed Exploration in Multi-Armed Bandits NIPS 2013
Large Scale Distributed Sparse Precision Estimation NIPS 2013
Streaming Variational Bayes NIPS 2013
Estimation, Optimization, and Parallelism when Data is Sparse NIPS 2013
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization NIPS 2012
Communication-Efficient Algorithms for Statistical Optimization NIPS 2012
Entangled Monte Carlo NIPS 2012
Large Scale Distributed Deep Networks NIPS 2012
Distributed Non-Stochastic Experts NIPS 2012
Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers AISTATS 2012