conftrace_

distributed optimization

275 papers

Explore in graph

Co-occurring keywords

federated learning (1333) communication efficiency (297) distributed learning (563) stochastic gradient descent (1091) convex optimization (1321) stochastic optimization (1060) communication complexity (99) variance reduction (523) communication compression (55) non-convex optimization (547)

Papers

Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning NIPS 2022
Distributed Distributionally Robust Optimization with Non-Convex Objectives NIPS 2022
Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques NIPS 2022
Beyond spectral gap: the role of the topology in decentralized learning NIPS 2022
Multi-Agent Multi-Armed Bandits with Limited Communication JMLR 2022
Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums ICML 2022
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization NIPS 2022
Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering NIPS 2022
Federated Learning with Partial Model Personalization ICML 2022
A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms ICML 2022
A Unified Analysis of Federated Learning with Arbitrary Client Participation NIPS 2022
Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM RSS 2022
Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization AISTATS 2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression NIPS 2022
Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity NIPS 2022
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox NIPS 2022
Asymptotic Network Independence and Step-Size for a Distributed Subgradient Method JMLR 2022
Learning Linear Models Using Distributed Iterative Hessian Sketching L4DC 2022
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond NIPS 2022
Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity NIPS 2022
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations NIPS 2022
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning CVPR 2022
Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022
Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time AISTATS 2022
Acceleration in Distributed Optimization under Similarity AISTATS 2022