distributed learning

Training Gaussian Mixture Models at Scale via Coresets JMLR 2018 A distributed block coordinate descent method for training l1 regularized linear classifiers JMLR 2017 Asynchronous Distributed Variational Gaussian Process for Regression ICML 2017 Asynchronous Stochastic Gradient Descent with Delay Compensation ICML 2017 Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NeurIPS 2017 Collaborative Deep Learning in Fixed Topology Networks NeurIPS 2017 Collaborative PAC Learning NeurIPS 2017 Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis ICML 2017 Communication-Efficient Distributed Learning of Discrete Distributions NeurIPS 2017 Communication-efficient Distributed Sparse Linear Discriminant Analysis AISTATS 2017 Communication-Efficient Learning of Deep Networks from Decentralized Data AISTATS 2017 Communication-efficient Sparse Regression JMLR 2017 Computational Limits of A Distributed Algorithm for Smoothing Spline JMLR 2017 Data Driven Resource Allocation for Distributed Learning AISTATS 2017 Differentially private Bayesian learning on distributed data NeurIPS 2017 Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server JMLR 2017 Distributed Learning with Regularized Least Squares JMLR 2017 Distributed Mean Estimation with Limited Communication ICML 2017 Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017 Efficient Distributed Learning with Sparsity ICML 2017 Gaia: Geo-Distributed Machine Learning Approaching LAN Speeds NSDI 2017 Gradient Coding: Avoiding Stragglers in Distributed Learning ICML 2017 Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network JMLR 2017 Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NeurIPS 2017 Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study IJCAI 2017