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2403.15146
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On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond
22 March 2024
Bohan Wang
Huishuai Zhang
Qi Meng
Ruoyu Sun
Zhi-Ming Ma
Wei Chen
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Papers citing
"On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond"
11 / 11 papers shown
Title
Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance
Qi Zhang
Yi Zhou
Shaofeng Zou
109
7
0
01 Apr 2024
Convergence of Adam for Non-convex Objectives: Relaxed Hyperparameters and Non-ergodic Case
Meixuan He
Yuqing Liang
Jinlan Liu
Dongpo Xu
61
9
0
20 Jul 2023
Convex and Non-convex Optimization Under Generalized Smoothness
Haochuan Li
Jian Qian
Yi Tian
Alexander Rakhlin
Ali Jadbabaie
70
44
0
02 Jun 2023
Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods
Junchi Yang
Xiang Li
Ilyas Fatkhullin
Niao He
74
17
0
21 May 2023
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance
Matthew Faw
Isidoros Tziotis
Constantine Caramanis
Aryan Mokhtari
Sanjay Shakkottai
Rachel A. Ward
67
61
0
11 Feb 2022
Improved Analysis of Clipping Algorithms for Non-convex Optimization
Bohang Zhang
Jikai Jin
Cong Fang
Liwei Wang
104
92
0
05 Oct 2020
A Simple Convergence Proof of Adam and Adagrad
Alexandre Défossez
Léon Bottou
Francis R. Bach
Nicolas Usunier
123
159
0
05 Mar 2020
Lower Bounds for Non-Convex Stochastic Optimization
Yossi Arjevani
Y. Carmon
John C. Duchi
Dylan J. Foster
Nathan Srebro
Blake E. Woodworth
93
362
0
05 Dec 2019
Why gradient clipping accelerates training: A theoretical justification for adaptivity
J.N. Zhang
Tianxing He
S. Sra
Ali Jadbabaie
80
467
0
28 May 2019
A Sufficient Condition for Convergences of Adam and RMSProp
Fangyu Zou
Li Shen
Zequn Jie
Weizhong Zhang
Wei Liu
63
372
0
23 Nov 2018
Convergence guarantees for RMSProp and ADAM in non-convex optimization and an empirical comparison to Nesterov acceleration
Soham De
Anirbit Mukherjee
Enayat Ullah
71
101
0
18 Jul 2018
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