Continuous Time Analysis of Momentum Methods

10 June 2019

Papers citing "Continuous Time Analysis of Momentum Methods"

12 / 12 papers shown

Title
Nesterov Acceleration for Ensemble Kalman Inversion and Variants Sydney Vernon Eviatar Bach Oliver R. A. Dunbar 44 1 0 15 Jan 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 137 1 0 08 Oct 2024
Who breaks early, looses: goal oriented training of deep neural networks based on port Hamiltonian dynamics Julian Burghoff Marc Heinrich Monells Hanno Gottschalk 14 0 0 14 Apr 2023
From Optimization to Sampling Through Gradient Flows Nicolas García Trillos B. Hosseini D. Sanz-Alonso 23 11 0 22 Feb 2023
On a continuous time model of gradient descent dynamics and instability in deep learning Mihaela Rosca Yan Wu Chongli Qin Benoit Dherin 16 6 0 03 Feb 2023
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent Avrajit Ghosh He Lyu Xitong Zhang Rongrong Wang 53 20 0 02 Feb 2023
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast Evasion of Non-Degenerate Saddle Points Mayank Baranwal Param Budhraja V. Raj A. Hota 33 2 0 07 Dec 2022
Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis Taiki Miyagawa 50 9 0 28 Oct 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Satyen Kale Jason D. Lee Chris De Sa Ayush Sekhari Karthik Sridharan 27 4 0 13 Oct 2022
A Continuous-time Stochastic Gradient Descent Method for Continuous Data Kexin Jin J. Latz Chenguang Liu Carola-Bibiane Schönlieb 20 9 0 07 Dec 2021
Heavy Ball Neural Ordinary Differential Equations Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 35 56 0 10 Oct 2021
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights Weijie Su Stephen P. Boyd Emmanuel J. Candes 108 1,154 0 04 Mar 2015