distributed optimization

Local Composite Saddle Point Optimization ICLR 2024 MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence NeurIPS 2024 Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity NeurIPS 2024 On Sampling Strategies for Spectral Model Sharding NeurIPS 2024 Optimization Algorithm Design via Electric Circuits NeurIPS 2024 Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition NeurIPS 2024 Personalized PCA: Decoupling Shared and Unique Features JMLR 2024 Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions AAAI 2024 Stabilized Proximal-Point Methods for Federated Optimization NeurIPS 2024 Towards Stability and Generalization Bounds in Decentralized Minibatch Stochastic Gradient Descent AAAI 2024 A^2CiD^2: Accelerating Asynchronous Communication in Decentralized Deep Learning NeurIPS 2023 Accelerated Primal-Dual Mirror Dynamics for Centralized and Distributed Constrained Convex Optimization Problems JMLR 2023 A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting NeurIPS 2023 Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity CVPR 2023 Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees JMLR 2023 Beyond Spectral Gap: The Role of the Topology in Decentralized Learning JMLR 2023 Byzantine-Tolerant Methods for Distributed Variational Inequalities NeurIPS 2023 Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation ICML 2023 DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity ICLR 2023 Decentralized Learning: Theoretical Optimality and Practical Improvements JMLR 2023 Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization NeurIPS 2023 Distributed Projection-Free Online Learning for Smooth and Convex Losses AAAI 2023 Distributed Sparse Regression via Penalization JMLR 2023 Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory AAAI 2023 EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression ICML 2023