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Distributed Learning

1100 directly classified papers

Papers per year

Papers

Better Together: Jointly Optimizing ML Collective Scheduling and Execution Planning using SYNDICATE NSDI 2023
Beyond Spectral Gap: The Role of the Topology in Decentralized Learning JMLR 2023
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning IJCAI 2023
Communication-Efficient Collaborative Best Arm Identification AAAI 2023
Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning UAI 2023
Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory AAAI 2023
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning JMLR 2023
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization AAAI 2023
Patch-Based Privacy Preserving Neural Network for Vision Tasks WACV 2023
Collaborative Learning via Prediction Consensus NIPS 2023
Momentum Provably Improves Error Feedback! NIPS 2023
Coordinating Distributed Example Orders for Provably Accelerated Training NIPS 2023
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning AAAI 2023
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer NIPS 2023
SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training NIPS 2022
Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information L4DC 2022
Anarchic Federated Learning ICML 2022
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning ICML 2022
Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation ICML 2022
Communication-efficient Distributed Learning for Large Batch Optimization ICML 2022
Detached Error Feedback for Distributed SGD with Random Sparsification ICML 2022
Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology ICML 2022
Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances ICML 2022
Learning Linear Models Using Distributed Iterative Hessian Sketching L4DC 2022