← Optimization & Theory
Machine Learning › Optimization & Theory ›

Distributed Learning

1100 directly classified papers

Papers per year

Papers

Distributed Minimum Error Entropy Algorithms JMLR 2020
Distributed Kernel Ridge Regression with Communications JMLR 2020
GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning JMLR 2020
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks NIPS 2020
Dual-Free Stochastic Decentralized Optimization with Variance Reduction NIPS 2020
WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions JMLR 2020
Decentralized Accelerated Proximal Gradient Descent NIPS 2020
Zeno++: Robust Fully Asynchronous SGD ICML 2020
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent JMLR 2020
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning NIPS 2020
Breaking the Communication-Privacy-Accuracy Trilemma NIPS 2020
Simultaneous Inference for Massive Data: Distributed Bootstrap ICML 2020
Distributed Feature Screening via Componentwise Debiasing JMLR 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction AISTATS 2020
Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent ICML 2020
Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study ICML 2020
From Local SGD to Local Fixed-Point Methods for Federated Learning ICML 2020
Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts NIPS 2020
Decentralised Learning with Random Features and Distributed Gradient Descent ICML 2020
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method NIPS 2020
Catching Cheats: Detecting Strategic Manipulation in Distributed Optimisation of Electric Vehicle Aggregators (Extended Abstract) IJCAI 2020
One-shot Distributed Ridge Regression in High Dimensions ICML 2020
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking ICML 2020
Federated Accelerated Stochastic Gradient Descent NIPS 2020
Quantized Decentralized Stochastic Learning over Directed Graphs ICML 2020