distributed optimization

Distributed Second Order Methods with Fast Rates and Compressed Communication ICML 2021 Distributed Zero-Order Optimization under Adversarial Noise NeurIPS 2021 Exponential Graph is Provably Efficient for Decentralized Deep Training NeurIPS 2021 FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization NeurIPS 2021 Federated Learning under Arbitrary Communication Patterns ICML 2021 Federated Learning with Compression: Unified Analysis and Sharp Guarantees AISTATS 2021 LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads AISTATS 2021 Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NeurIPS 2021 Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NeurIPS 2021 Linear Convergent Decentralized Optimization with Compression ICLR 2021 LocalNewton: Reducing communication rounds for distributed learning UAI 2021 Local SGD: Unified Theory and New Efficient Methods AISTATS 2021 Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices NeurIPS 2021 Multi-agent Approach to Resource Allocation in Autonomous Vehicle Fleets IJCAI 2021 Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks ICLR 2021 Near Optimal Distributed Learning of Halfspaces with Two Parties COLT 2021 Newton Method over Networks is Fast up to the Statistical Precision ICML 2021 One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them JMLR 2021 On the Convergence of Communication-Efficient Local SGD for Federated Learning AAAI 2021 Optimal Algorithms for Submodular Maximization with Distributed Constraints L4DC 2021 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data ICML 2021 Sageflow: Robust Federated Learning against Both Stragglers and Adversaries NeurIPS 2021 Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021 Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization NeurIPS 2021 The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication COLT 2021