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Distributed Learning

1100 directly classified papers

Papers per year

Papers

Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation ICML 2023
On-Demand Communication for Asynchronous Multi-Agent Bandits AISTATS 2023
Fleet Active Learning: A Submodular Maximization Approach CORL 2023
On the Convergence of Federated Averaging with Cyclic Client Participation ICML 2023
Differentially Private Distributed Bayesian Linear Regression with MCMC ICML 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning ICML 2023
The communication cost of security and privacy in federated frequency estimation AISTATS 2023
ERM-KTP: Knowledge-Level Machine Unlearning via Knowledge Transfer CVPR 2023
Elastic Aggregation for Federated Optimization CVPR 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data ICML 2023
Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost ICML 2023
Federated learning of models pre-trained on different features with consensus graphs UAI 2023
BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models ICML 2023
DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training CVPR 2023
Federated Learning With Data-Agnostic Distribution Fusion CVPR 2023
Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning NIPS 2023
Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs NSDI 2023
Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity AISTATS 2023
TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training Jobs NSDI 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023
Incremental Aggregated Riemannian Gradient Method for Distributed PCA AISTATS 2023
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout AISTATS 2023
Accelerated Primal-Dual Mirror Dynamics for Centralized and Distributed Constrained Convex Optimization Problems JMLR 2023
Distributed Sparse Regression via Penalization JMLR 2023