Distributed Learning

Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NeurIPS 2015 Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care NeurIPS 2015 Communication Complexity of Distributed Convex Learning and Optimization NeurIPS 2015 Deep learning with Elastic Averaging SGD NeurIPS 2015 DiSCO: Distributed Optimization for Self-Concordant Empirical Loss ICML 2015 Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM ICML 2015 Distributed Gaussian Processes ICML 2015 Distributed Matrix Completion and Robust Factorization JMLR 2015 Distributed Submodular Cover: Succinctly Summarizing Massive Data NeurIPS 2015 Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates JMLR 2015 Extending Gossip Algorithms to Distributed Estimation of U-statistics NeurIPS 2015 FaLRR: A Fast Low Rank Representation Solver CVPR 2015 Fast Distributed k-Center Clustering with Outliers on Massive Data NeurIPS 2015 Hashing for Distributed Data ICML 2015 Large-scale Distributed Dependent Nonparametric Trees ICML 2015 On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants NeurIPS 2015 Parallelizing MCMC with Random Partition Trees NeurIPS 2015 SAMOA: Scalable Advanced Massive Online Analysis JMLR 2015 Secure Multi-party Differential Privacy NeurIPS 2015 Streaming, Distributed Variational Inference for Bayesian Nonparametrics NeurIPS 2015 Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms NeurIPS 2015 The Power of Randomization: Distributed Submodular Maximization on Massive Datasets ICML 2015 Variational Consensus Monte Carlo NeurIPS 2015 A Reliable Effective Terascale Linear Learning System JMLR 2014 Asynchronous Distributed ADMM for Consensus Optimization ICML 2014