Distributed Learning

Checkmate: Zero Performance Overhead Model Checkpointing via Network Gradient Replication NSDI 2026 Communication-Efficient Distributed Training for Collaborative Flat Optima Recovery in Deep Learning UAI 2026 Di-PS: System-Algorithm Co-Design for Asynchronous and Heterogeneous Cross-cluster LLM Training at Scale NSDI 2026 Hetu v2: A General and Scalable Deep Learning System with Hierarchical and Heterogeneous Single Program Multiple Data Annotations OSDI 2026 OptiCo: Adaptive Distributed Training Optimization via Collaborative Agent Reasoning ACL 2026 Phantora: Maximizing Code Reuse in Simulation-based Machine Learning System Performance Estimation NSDI 2026 SYMI: Efficient Mixture-of-Experts Training via Model and Optimizer State Decoupling NSDI 2026 TrainMover: An Interruption-Resilient Runtime for ML Training OSDI 2026 UEP: Portable Expert-Parallel Communication OSDI 2026 Addressing Label Shift in Distributed Learning via Entropy Regularization​ ICLR 2025 Convergence of Distributed Adaptive Optimization with Local Updates ICLR 2025 Generalization and Distributed Learning of GFlowNets ICLR 2025 How to Recover Long Audio Sequences Through Gradient Inversion Attack With Dynamic Segment-based Reconstruction Interspeech 2025 Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression ICLR 2025 Optimal Distributed Training With Co-Adaptive Data Parallelism in Heterogeneous Environments IJCAI 2025 Scalability Enhancement and Data-Heterogeneity Awareness in Gradient Tracking based Decentralized Bayesian Learning L4DC 2025 Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs AISTATS 2025 ZEN: Empowering Distributed Training with Sparsity-driven Data Synchronization OSDI 2025 Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform ICLR 2024 DOGS: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction Via Gaussian Consensus NeurIPS 2024 Exponential Quantum Communication Advantage in Distributed Inference and Learning NeurIPS 2024 LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing NeurIPS 2024 On the Effect of Batch Size in Byzantine-Robust Distributed Learning ICLR 2024 SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores ICLR 2024 A^2CiD^2: Accelerating Asynchronous Communication in Decentralized Deep Learning NeurIPS 2023