Convex and Non-convex Optimization Under Generalized Smoothness

Convex and Non-convex Optimization Under Generalized Smoothness

2 June 2023

Alexander Rakhlin

Papers citing "Convex and Non-convex Optimization Under Generalized Smoothness"

19 / 19 papers shown

Title
SAD Neural Networks: Divergent Gradient Flows and Asymptotic Optimality via o-minimal Structures Julian Kranz Davide Gallon Steffen Dereich Arnulf Jentzen 36 0 0 14 May 2025
On the Convergence of Adam-Type Algorithm for Bilevel Optimization under Unbounded Smoothness Xiaochuan Gong Jie Hao Mingrui Liu 68 0 0 05 Mar 2025
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond Weiyu Chen Xiaoyuan Zhang Baijiong Lin Xi Lin Han Zhao Qingfu Zhang James T. Kwok 86 4 0 19 Jan 2025
Understanding Adam Requires Better Rotation Dependent Assumptions Lucas Maes Tianyue H. Zhang Alexia Jolicoeur-Martineau Ioannis Mitliagkas Damien Scieur Simon Lacoste-Julien Charles Guille-Escuret 40 3 0 25 Oct 2024
Error Feedback under $(L_0,L_1)$ -Smoothness: Normalization and Momentum Sarit Khirirat Abdurakhmon Sadiev Artem Riabinin Eduard A. Gorbunov Peter Richtárik 32 0 0 22 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 68 0 0 08 Oct 2024
Recent Advances in Non-convex Smoothness Conditions and Applicability to Deep Linear Neural Networks Vivak Patel Christian Varner 33 0 0 20 Sep 2024
Empirical Tests of Optimization Assumptions in Deep Learning Hoang Tran Qinzi Zhang Ashok Cutkosky 49 1 0 01 Jul 2024
Scalable Optimization in the Modular Norm Tim Large Yang Liu Minyoung Huh Hyojin Bahng Phillip Isola Jeremy Bernstein 59 13 0 23 May 2024
Almost sure convergence rates of stochastic gradient methods under gradient domination Simon Weissmann Sara Klein Waïss Azizian Leif Döring 44 3 0 22 May 2024
The Challenges of Optimization For Data Science Christian Varner Vivak Patel 42 1 0 15 Apr 2024
On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond Bohan Wang Huishuai Zhang Qi Meng Ruoyu Sun Zhi-Ming Ma Wei Chen 48 9 0 22 Mar 2024
Directional Smoothness and Gradient Methods: Convergence and Adaptivity Aaron Mishkin Ahmed Khaled Yuanhao Wang Aaron Defazio Robert Mansel Gower 56 6 0 06 Mar 2024
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity Wenzhi Gao Qi Deng 32 1 0 25 Jan 2024
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis Jie Hao Xiaochuan Gong Mingrui Liu 40 7 0 17 Jan 2024
Parameter-Agnostic Optimization under Relaxed Smoothness Florian Hübler Junchi Yang Xiang Li Niao He 51 14 0 06 Nov 2023
A Novel Gradient Methodology with Economical Objective Function Evaluations for Data Science Applications Christian Varner Vivak Patel 36 2 0 19 Sep 2023
Convergence of Adam Under Relaxed Assumptions Haochuan Li Alexander Rakhlin Ali Jadbabaie 42 57 0 27 Apr 2023
Acceleration Methods Alexandre d’Aspremont Damien Scieur Adrien B. Taylor 287 120 0 23 Jan 2021