conftrace_

momentum method

75 papers

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Co-occurring keywords

stochastic gradient descent (1091) convergence rate (607) gradient descent (1144) stochastic optimization (1060) non-convex optimization (547) nonconvex optimization (316) convergence analysis (395) variance reduction (523) convex optimization (1321) nesterov acceleration (54)

Papers

Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions NIPS 2022
A Stochastic Momentum Accelerated Quasi-Newton Method for Neural Networks (Student Abstract) AAAI 2022
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum L4DC 2022
Gradient Temporal Difference with Momentum: Stability and Convergence AAAI 2022
On the Last Iterate Convergence of Momentum Methods ALT 2022
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization ICML 2022
Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters ICML 2022
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out ICML 2022
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity AAAI 2022
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization JMLR 2022
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization AISTATS 2022
MDPGT: Momentum-Based Decentralized Policy Gradient Tracking AAAI 2022
Super-Acceleration with Cyclical Step-sizes AISTATS 2022
Stochastic Sign Descent Methods: New Algorithms and Better Theory ICML 2021
Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization IJCAI 2021
Continuous Time Analysis of Momentum Methods JMLR 2021
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning NIPS 2021
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models NIPS 2021
The Power of Factorial Powers: New Parameter settings for (Stochastic) Optimization ACML 2021
On the Faster Alternating Least-Squares for CCA AISTATS 2021
Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness ICML 2021
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients NIPS 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NIPS 2021
Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization NIPS 2021
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems NIPS 2021