On the Convergence Proof of AMSGrad and a New Version

7 April 2019

Papers citing "On the Convergence Proof of AMSGrad and a New Version"

11 / 11 papers shown

Title
Investigation of Energy-efficient AI Model Architectures and Compression Techniques for "Green" Fetal Brain Segmentation Szymon Mazurek M. Pytlarz Sylwia Malec A. Crimi 37 0 0 03 Apr 2024
How Free is Parameter-Free Stochastic Optimization? Amit Attia Tomer Koren ODL 47 5 0 05 Feb 2024
SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance Amit Attia Tomer Koren ODL 22 26 0 17 Feb 2023
HesScale: Scalable Computation of Hessian Diagonals Mohamed Elsayed A. R. Mahmood 22 8 0 20 Oct 2022
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize Ali Kavis Kfir Y. Levy V. Cevher 25 41 0 06 Apr 2022
An Empirical Review of Optimization Techniques for Quantum Variational Circuits Owen Lockwood 29 16 0 03 Feb 2022
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization Problems Babak Barazandeh Tianjian Huang George Michailidis 32 12 0 10 Jun 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 28 7 0 16 Feb 2021
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers Robin M. Schmidt Frank Schneider Philipp Hennig ODL 40 162 0 03 Jul 2020
Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball Othmane Sebbouh Robert Mansel Gower Aaron Defazio 13 22 0 14 Jun 2020
Iterative Averaging in the Quest for Best Test Error Diego Granziol Xingchen Wan Samuel Albanie Stephen J. Roberts 10 3 0 02 Mar 2020