distributed optimization

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging NeurIPS 2022 Multi-Agent Multi-Armed Bandits with Limited Communication JMLR 2022 On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond NeurIPS 2022 On Distributed Adaptive Optimization with Gradient Compression ICLR 2022 On the Convergence of Decentralized Adaptive Gradient Methods ACML 2022 Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity NeurIPS 2022 Permutation Compressors for Provably Faster Distributed Nonconvex Optimization ICLR 2022 Personalized Federated Learning with Contextualized Generalization IJCAI 2022 Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques NeurIPS 2022 Towards Optimal Communication Complexity in Distributed Non-Convex Optimization NeurIPS 2022 Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning NeurIPS 2022 A Distributed Method for Fitting Laplacian Regularized Stratified Models JMLR 2021 A Stochastic Newton Algorithm for Distributed Convex Optimization NeurIPS 2021 Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning IJCAI 2021 Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning ICML 2021 Breaking the centralized barrier for cross-device federated learning NeurIPS 2021 Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data ICML 2021 Byzantine-Resilient Non-Convex Stochastic Gradient Descent ICLR 2021 CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NeurIPS 2021 Communication-Efficient Distributed Optimization with Quantized Preconditioners ICML 2021 Communication-efficient SGD: From Local SGD to One-Shot Averaging NeurIPS 2021 Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization COLT 2021 DeepLM: Large-Scale Nonlinear Least Squares on Deep Learning Frameworks Using Stochastic Domain Decomposition CVPR 2021 Distributed Machine Learning with Sparse Heterogeneous Data NeurIPS 2021 Distributed Saddle-Point Problems Under Data Similarity NeurIPS 2021