distributed optimization

SIFAR: A Simple Faster Accelerated Variance-Reduced Gradient Method IJCAI 2025 Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology AAAI 2025 Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks ICLR 2024 Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes NeurIPS 2024 Adaptive Federated Minimax Optimization with Lower Complexities AISTATS 2024 A deep learning approach for distributed aggregative optimization with users’ Feedback L4DC 2024 A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs NeurIPS 2024 A Huber Loss Minimization Approach to Byzantine Robust Federated Learning AAAI 2024 AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms AISTATS 2024 Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation AAAI 2024 Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates AISTATS 2024 Communication Efficient Distributed Newton Method over Unreliable Networks AAAI 2024 Convergence Analysis of Inexact Over-relaxed ADMM via Dissipativity Theory ACML 2024 Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold ICLR 2024 Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization ICLR 2024 Distributed Estimation on Semi-Supervised Generalized Linear Model JMLR 2024 EControl: Fast Distributed Optimization with Compression and Error Control ICLR 2024 Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization CVPR 2024 Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction NeurIPS 2024 Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression AISTATS 2024 Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations NeurIPS 2024 Hierarchical Federated Learning with Multi-Timescale Gradient Correction NeurIPS 2024 High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise ICML 2024 iMESA: Incremental Distributed Optimization for Collaborative Simultaneous Localization and Mapping RSS 2024 Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NeurIPS 2024