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distributed learning

563 papers

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Also known as

DL-DCL DML

Co-occurring keywords

federated learning (1320) stochastic gradient descent (1088) communication efficiency (297) distributed optimization (275) stochastic optimization (1060) decentralized optimization (113) communication complexity (99) distributed training (187) gradient compression (78) gradient descent (1143)

Papers

Gradient Coding: Avoiding Stragglers in Distributed Learning ICML 2017
Distributed Mean Estimation with Limited Communication ICML 2017
Asynchronous Distributed Variational Gaussian Process for Regression ICML 2017
Computational Limits of A Distributed Algorithm for Smoothing Spline JMLR 2017
Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017
Communication-efficient Sparse Regression JMLR 2017
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NIPS 2017
Collaborative Deep Learning in Fixed Topology Networks NIPS 2017
Distributed Multi-Task Learning AISTATS 2016
DSA: Decentralized Double Stochastic Averaging Gradient Algorithm JMLR 2016
A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016
Distributed Clustering of Linear Bandits in Peer to Peer Networks ICML 2016
Training Neural Networks Without Gradients: A Scalable ADMM Approach ICML 2016
Communication Efficient Distributed Agnostic Boosting AISTATS 2016
DECOrrelated feature space partitioning for distributed sparse regression NIPS 2016
Scalable Gaussian Process Classification via Expectation Propagation AISTATS 2016
Bootstrap Model Aggregation for Distributed Statistical Learning NIPS 2016
Latent Space Inference of Internet-Scale Networks JMLR 2016
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale NIPS 2016
Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation AISTATS 2016
Feature-distributed sparse regression: a screen-and-clean approach NIPS 2016
d-VMP: Distributed Variational Message Passing PGM 2016
Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks AISTATS 2016
Asynchronous Parallel Learning for Neural Networks and Structured Models with Dense Features COLING 2016
Communication Complexity of Distributed Convex Learning and Optimization NIPS 2015