Continuous-time Models for Stochastic Optimization Algorithms

Continuous-time Models for Stochastic Optimization Algorithms

5 October 2018

Antonio Orvieto

Aurelien Lucchi

Papers citing "Continuous-time Models for Stochastic Optimization Algorithms"

9 / 9 papers shown

Title
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 137 1 0 08 Oct 2024
An SDE for Modeling SAM: Theory and Insights Enea Monzio Compagnoni Luca Biggio Antonio Orvieto F. Proske Hans Kersting Aurelien Lucchi 23 13 0 19 Jan 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
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
Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective Xinwei Zhang Mingyi Hong N. Elia FedML 13 3 0 27 Apr 2022
Free-rider Attacks on Model Aggregation in Federated Learning Yann Fraboni Richard Vidal Marco Lorenzi FedML 6 124 0 21 Jun 2020
Shadowing Properties of Optimization Algorithms Antonio Orvieto Aurelien Lucchi 30 18 0 12 Nov 2019
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,199 0 16 Aug 2016
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