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Distributed Learning

157 papers

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Papers

Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks ICML 2017
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017
Distributed Mean Estimation with Limited Communication ICML 2017
Gradient Coding: Avoiding Stragglers in Distributed Learning ICML 2017
Projection-free Distributed Online Learning in Networks ICML 2017
Distributed Accelerated Proximal Coordinate Gradient Methods IJCAI 2017
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction AISTATS 2016
A Consensus-Based Framework for Distributed Bundle Adjustment CVPR 2016
DSA: Decentralized Double Stochastic Averaging Gradient Algorithm JMLR 2016
d-VMP: Distributed Variational Message Passing PGM 2016
DiSCO: Distributed Optimization for Self-Concordant Empirical Loss ICML 2015
Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds ICML 2015
An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization ICML 2015
Communication-Efficient Distributed Dual Coordinate Ascent NIPS 2014
Large-scale L-BFGS using MapReduce NIPS 2014
Parallel Direction Method of Multipliers NIPS 2014
Communication-Efficient Distributed Optimization using an Approximate Newton-type Method ICML 2014
Large Scale Distributed Sparse Precision Estimation NIPS 2013
Distributed $k$-means and $k$-median Clustering on General Topologies NIPS 2013
Optimistic Concurrency Control for Distributed Unsupervised Learning NIPS 2013
Information-theoretic lower bounds for distributed statistical estimation with communication constraints NIPS 2013
Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent NIPS 2013
Distributed Non-Stochastic Experts NIPS 2012
Large Scale Distributed Deep Networks NIPS 2012
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization NIPS 2012