Distributed Learning

Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD JMLR 2023 Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning NeurIPS 2023 Robust and Actively Secure Serverless Collaborative Learning NeurIPS 2023 Robust Collaborative Learning with Linear Gradient Overhead ICML 2023 Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity NeurIPS 2023 Robust Heterogeneous Federated Learning under Data Corruption ICCV 2023 Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract) IJCAI 2023 Scalable Distributed Massive MIMO Baseband Processing NSDI 2023 Scaling Up Models and Data with t5x and seqio JMLR 2023 Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning AAAI 2023 Sequential Gradient Coding For Straggler Mitigation ICLR 2023 SLAMB: Accelerated Large Batch Training with Sparse Communication ICML 2023 Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm NeurIPS 2023 StarryNet: Empowering Researchers to Evaluate Futuristic Integrated Space and Terrestrial Networks NSDI 2023 Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis NeurIPS 2023 SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient ICML 2023 SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication ICLR 2023 TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches NSDI 2023 Task-aware Distributed Source Coding under Dynamic Bandwidth NeurIPS 2023 The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond ICML 2023 The communication cost of security and privacy in federated frequency estimation AISTATS 2023 Top-k data selection via distributed sample quantile inference L4DC 2023 TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training Jobs NSDI 2023 Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning NeurIPS 2023 Towards Sharp Analysis for Distributed Learning with Random Features IJCAI 2023