{"total":24,"rows":[{"id":"2409.03137","title":"The AdEMAMix Optimizer: Better, Faster, Older","created":"2024-09-05","cited_by_count":54,"area":null},{"id":"2104.11981","title":"DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training","created":"2021-04-24","cited_by_count":40,"area":null},{"id":"2307.15196","title":"The Marginal Value of Momentum for Small Learning Rate SGD","created":"2023-07-27","cited_by_count":18,"area":null},{"id":"2206.11124","title":"A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta","created":"2022-06-22","cited_by_count":11,"area":null},{"id":"2202.03525","title":"Nesterov Accelerated Shuffling Gradient Method for Convex Optimization","created":"2022-02-07","cited_by_count":10,"area":null},{"id":"2604.14108","title":"Momentum Further Constrains Sharpness at the Edge of Stochastic Stability","created":"2026-04-15","cited_by_count":10,"area":null},{"id":"2203.01744","title":"Accelerated SGD for Non-Strongly-Convex Least Squares","created":"2022-03-03","cited_by_count":9,"area":null},{"id":"2312.14567","title":"Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise","created":"2023-12-22","cited_by_count":9,"area":null},{"id":"2107.04197","title":"REX: Revisiting Budgeted Training with an Improved Schedule","created":"2021-07-09","cited_by_count":8,"area":null},{"id":"2110.09057","title":"Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization","created":"2021-10-18","cited_by_count":8,"area":null},{"id":"2406.12774","title":"Towards Exact Gradient-based Training on Analog In-memory Computing","created":"2024-06-18","cited_by_count":7,"area":null},{"id":"2203.16723","title":"Exploiting Explainable Metrics for Augmented SGD","created":"2022-03-31","cited_by_count":2,"area":null},{"id":"2406.13041","title":"Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum","created":"2024-06-18","cited_by_count":2,"area":null},{"id":"2205.13711","title":"Incorporating the Barzilai-Borwein Adaptive Step Size into Sugradient Methods for Deep Network Training","created":"2022-05-27","cited_by_count":1,"area":null},{"id":"2209.11920","title":"Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms","created":"2022-09-24","cited_by_count":1,"area":null},{"id":"2303.17885","title":"Accelerating Wireless Federated Learning via Nesterov's Momentum and Distributed Principle Component Analysis","created":"2023-03-31","cited_by_count":1,"area":null},{"id":"2403.03180","title":"Shuffling Momentum Gradient Algorithm for Convex Optimization","created":"2024-03-05","cited_by_count":1,"area":null},{"id":"2404.06516","title":"Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games","created":"2024-04-04","cited_by_count":1,"area":null},{"id":"2511.02657","title":"A Byzantine-Robust Federated Learning with Nesterov Momentum","created":"2025-11-04","cited_by_count":1,"area":null},{"id":"2605.04269","title":"Adapt or Forget: Provable Tradeoffs Between Adam and SGD in Nonstationary Optimization","created":"2026-05-05","cited_by_count":1,"area":null},{"id":"2110.15547","title":"Does Momentum Help? A Sample Complexity Analysis","created":"2021-10-29","cited_by_count":0,"area":null},{"id":"2401.01579","title":"An Invariant Information Geometric Method for High-Dimensional Online Optimization","created":"2024-01-03","cited_by_count":0,"area":null},{"id":"2601.12931","title":"Online Continual Learning for Time Series: a Natural Score-driven Approach","created":"2026-01-19","cited_by_count":0,"area":null},{"id":"2610.20413","title":"When Does Momentum Help in Reinforcement Learning with Verifiable Rewards?","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}