Distributed Learning

Distributed Probabilistic Learning for Camera Networks with Missing Data NeurIPS 2012 Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers AISTATS 2012 Entangled Monte Carlo NeurIPS 2012 Large Scale Distributed Deep Networks NeurIPS 2012 Protocols for Learning Classifiers on Distributed Data AISTATS 2012 Distributed Delayed Stochastic Optimization NeurIPS 2011 Divide-and-Conquer Matrix Factorization NeurIPS 2011 Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NeurIPS 2011 Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011 A Streaming Parallel Decision Tree Algorithm JMLR 2010 Consensus-Based Distributed Support Vector Machines JMLR 2010 Distributed Dual Averaging In Networks NeurIPS 2010 Distributed Optimization with Pairwise Constraints and its Application to Multi-robot Path Planning RSS 2010 Parallelized Stochastic Gradient Descent NeurIPS 2010 Preliminary Results in Decentralized Estimation for Single-Beacon Acoustic Underwater Navigation RSS 2010 Distributed Algorithms for Topic Models JMLR 2009 Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models NeurIPS 2009 Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process NeurIPS 2009 Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units NeurIPS 2009 Slow Learners are Fast NeurIPS 2009 A Massively Parallel Digital Learning Processor NeurIPS 2008 A Scalable Hierarchical Distributed Language Model NeurIPS 2008 Asynchronous Distributed Learning of Topic Models NeurIPS 2008 Distributed Inference for Latent Dirichlet Allocation NeurIPS 2007 Parallelizing Support Vector Machines on Distributed Computers NeurIPS 2007