conftrace_

communication efficiency

297 papers

Explore in graph

Co-occurring keywords

federated learning (1333) distributed learning (563) distributed optimization (275) stochastic gradient descent (1091) model compression (3302) gradient compression (78) distributed training (188) stochastic optimization (1060) differential privacy (1016) decentralized learning (103)

Papers

LocalNewton: Reducing communication rounds for distributed learning UAI 2021
Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms JMLR 2021
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NIPS 2021
Step-Ahead Error Feedback for Distributed Training with Compressed Gradient AAAI 2021
DecentLaM: Decentralized Momentum SGD for Large-Batch Deep Training ICCV 2021
A Flexible Framework for Communication-Efficient Machine Learning AAAI 2021
On the Convergence of Communication-Efficient Local SGD for Federated Learning AAAI 2021
DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate AISTATS 2020
Distributionally Robust Federated Averaging NIPS 2020
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization ICML 2020
Moniqua: Modulo Quantized Communication in Decentralized SGD ICML 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020
A Double Residual Compression Algorithm for Efficient Distributed Learning AISTATS 2020
Practical Low-Rank Communication Compression in Decentralized Deep Learning NIPS 2020
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training NIPS 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy AISTATS 2020
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond JMLR 2020
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs AISTATS 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Breaking the Communication-Privacy-Accuracy Trilemma NIPS 2020
GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning JMLR 2020
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems AAAI 2020
Communication-Efficient Distributed PCA by Riemannian Optimization ICML 2020
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization AISTATS 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction AISTATS 2020