{"total":16,"rows":[{"id":"2502.00775","title":"ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning","created":"2025-02-02","cited_by_count":5,"area":null},{"id":"2509.22860","title":"Ringleader ASGD: The First Asynchronous SGD with Optimal Time Complexity under Data Heterogeneity","created":"2025-09-26","cited_by_count":5,"area":null},{"id":"2502.08206","title":"Optimizing Asynchronous Federated Learning: A Delicate Trade-Off Between Model-Parameter Staleness and Update Frequency","created":"2025-02-12","cited_by_count":2,"area":null},{"id":"2601.19379","title":"Optimal Asynchronous Stochastic Nonconvex Optimization under Heavy-Tailed Noise","created":"2026-01-27","cited_by_count":2,"area":null},{"id":"2605.13434","title":"Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity","created":"2026-05-13","cited_by_count":2,"area":null},{"id":"2605.18174","title":"Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method","created":"2026-05-18","cited_by_count":2,"area":null},{"id":"2605.20866","title":"LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2503.13795","title":"BurTorch: Revisiting Training from First Principles by Coupling Autodiff, Math Optimization, and Systems","created":"2025-03-18","cited_by_count":0,"area":null},{"id":"2601.12322","title":"Ordered Local Momentum for Asynchronous Distributed Learning under Arbitrary Delays","created":"2026-01-18","cited_by_count":0,"area":null},{"id":"2602.03802","title":"Do We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods","created":"2026-02-03","cited_by_count":0,"area":null},{"id":"2603.26231","title":"Optimization Trade-offs in Asynchronous Federated Learning: A Stochastic Networks Approach","created":"2026-03-27","cited_by_count":0,"area":null},{"id":"2605.02043","title":"Bringing Order to Asynchronous SGD: Towards Optimality under Data-Dependent Delays with Momentum","created":"2026-05-03","cited_by_count":0,"area":null},{"id":"2605.08871","title":"Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2606.13287","title":"Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers","created":"2026-06-11","cited_by_count":0,"area":null},{"id":"2606.30634","title":"One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2609.39357","title":"Robustifying Asynchronous SGD via Soft Throttling","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}