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Distributed Learning

1100 directly classified papers

Papers per year

Papers

A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization JMLR 2017
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server JMLR 2017
Distributed Adaptive Sampling for Kernel Matrix Approximation AISTATS 2017
Communication-efficient Distributed Sparse Linear Discriminant Analysis AISTATS 2017
Data Driven Resource Allocation for Distributed Learning AISTATS 2017
Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch Prox COLT 2017
Gaia: Geo-Distributed Machine Learning Approaching LAN Speeds NSDI 2017
Sparse Communication for Distributed Gradient Descent EMNLP 2017
Effective Parallelisation for Machine Learning NIPS 2017
Asynchronous Parallel Coordinate Minimization for MAP Inference NIPS 2017
Coded Distributed Computing for Inverse Problems NIPS 2017
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NIPS 2017
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NIPS 2017
Straggler Mitigation in Distributed Optimization Through Data Encoding NIPS 2017
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study IJCAI 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data AISTATS 2017
Decentralized Collaborative Learning of Personalized Models over Networks AISTATS 2017
Projection-free Distributed Online Learning in Networks ICML 2017
Efficient Distributed Learning with Sparsity ICML 2017
Gradient Coding: Avoiding Stragglers in Distributed Learning ICML 2017
Distributed Mean Estimation with Limited Communication ICML 2017
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis ICML 2017
Tux²: Distributed Graph Computation for Machine Learning NSDI 2017
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network JMLR 2017