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Distributed Learning

1100 directly classified papers

Papers per year

Papers

On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning AAAI 2020
Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions JMLR 2020
Near-Optimal Latency Versus Cost Tradeoffs in Geo-Distributed Storage NSDI 2020
Doubly Distributed Supervised Learning and Inference with High-Dimensional Correlated Outcomes JMLR 2020
Throughput-Optimal Topology Design for Cross-Silo Federated Learning NIPS 2020
Is Local SGD Better than Minibatch SGD? ICML 2020
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization ICML 2020
A High-Speed Load-Balancer Design with Guaranteed Per-Connection-Consistency NSDI 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks ICML 2020
Scalable and Flexible Clustering of Grouped Data via Parallel and Distributed Sampling in Versatile Hierarchical Dirichlet Processes UAI 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
DINO: Distributed Newton-Type Optimization Method ICML 2020
FedBoost: A Communication-Efficient Algorithm for Federated Learning ICML 2020
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020
The Non-IID Data Quagmire of Decentralized Machine Learning ICML 2020
Communication-Efficient Distributed PCA by Riemannian Optimization ICML 2020
Uncertain multi-agent MILPs: A data-driven decentralized solution with probabilistic feasibility guarantees L4DC 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization ICML 2020
Twine: A Unified Cluster Management System for Shared Infrastructure OSDI 2020
Mutual Transfer Learning for Massive Data ICML 2020
Online Convex Optimization Over Erdos-Renyi Random Networks NIPS 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020
Robust Federated Learning: The Case of Affine Distribution Shifts NIPS 2020
Apache Mahout: Machine Learning on Distributed Dataflow Systems JMLR 2020