distributed optimization

Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox NeurIPS 2022 Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization AISTATS 2022 Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering NeurIPS 2022 Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022 Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach ICLR 2022 Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM RSS 2022 Distributed Distributionally Robust Optimization with Non-Convex Objectives NeurIPS 2022 Distributed Online Convex Optimization with Compressed Communication NeurIPS 2022 Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity NeurIPS 2022 Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima JMLR 2022 EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization NeurIPS 2022 Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning NeurIPS 2022 Federated Functional Gradient Boosting AISTATS 2022 Federated Learning with Buffered Asynchronous Aggregation AISTATS 2022 Federated Learning with Partial Model Personalization ICML 2022 FedScale: Benchmarking Model and System Performance of Federated Learning at Scale ICML 2022 FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning AISTATS 2022 GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations NeurIPS 2022 Global Convergence of Federated Learning for Mixed Regression NeurIPS 2022 Hybrid Local SGD for Federated Learning with Heterogeneous Communications ICLR 2022 IntSGD: Adaptive Floatless Compression of Stochastic Gradients ICLR 2022 Learning Linear Models Using Distributed Iterative Hessian Sketching L4DC 2022 Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning CVPR 2022 Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time AISTATS 2022 Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression NeurIPS 2022