Direct Runge-Kutta Discretization Achieves Acceleration

Direct Runge-Kutta Discretization Achieves Acceleration

1 May 2018

Papers citing "Direct Runge-Kutta Discretization Achieves Acceleration"

12 / 12 papers shown

Title
Accelerating optimization over the space of probability measures Shi Chen Wenxuan Wu Yuhang Yao Stephen J. Wright 29 4 0 06 Oct 2023
Reducing Discretization Error in the Frank-Wolfe Method Zhaoyue Chen Yifan Sun 21 1 0 04 Apr 2023
Optimization using Parallel Gradient Evaluations on Multiple Parameters Yash Chandak Shiv Shankar V. Gandikota Philip S. Thomas A. Mazumdar 14 0 0 06 Feb 2023
A More Stable Accelerated Gradient Method Inspired by Continuous-Time Perspective Yasong Feng Weiguo Gao 23 0 0 09 Dec 2021
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization Peiyuan Zhang Antonio Orvieto Hadi Daneshmand Thomas Hofmann Roy S. Smith 27 9 0 23 Feb 2021
On dissipative symplectic integration with applications to gradient-based optimization G. Francca Michael I. Jordan René Vidal 19 47 0 15 Apr 2020
Shadowing Properties of Optimization Algorithms Antonio Orvieto Aurelien Lucchi 30 18 0 12 Nov 2019
Continuous Time Analysis of Momentum Methods Nikola B. Kovachki Andrew M. Stuart 17 32 0 10 Jun 2019
Understanding the Acceleration Phenomenon via High-Resolution Differential Equations Bin Shi S. Du Michael I. Jordan Weijie J. Su 17 251 0 21 Oct 2018
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective Filip Tronarp Hans Kersting Simo Särkkä Philipp Hennig 25 63 0 08 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 16 31 0 05 Oct 2018
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