ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.02409
  4. Cited By
On the Promise of the Stochastic Generalized Gauss-Newton Method for
  Training DNNs

On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs

3 June 2020
Matilde Gargiani
Andrea Zanelli
Moritz Diehl
Frank Hutter
    ODL
ArXivPDFHTML

Papers citing "On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs"

12 / 12 papers shown
Title
Incremental Gauss-Newton Descent for Machine Learning
Incremental Gauss-Newton Descent for Machine Learning
Mikalai Korbit
Mario Zanon
ODL
17
0
0
10 Aug 2024
Exact Gauss-Newton Optimization for Training Deep Neural Networks
Exact Gauss-Newton Optimization for Training Deep Neural Networks
Mikalai Korbit
Adeyemi Damilare Adeoye
Alberto Bemporad
Mario Zanon
ODL
33
0
0
23 May 2024
Thermodynamic Natural Gradient Descent
Thermodynamic Natural Gradient Descent
Kaelan Donatella
Samuel Duffield
Maxwell Aifer
Denis Melanson
Gavin Crooks
Patrick J. Coles
28
3
0
22 May 2024
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
S. Reifenstein
T. Leleu
Yoshihisa Yamamoto
48
1
0
02 May 2024
A Selective Review on Statistical Methods for Massive Data Computation:
  Distributed Computing, Subsampling, and Minibatch Techniques
A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques
Xuetong Li
Yuan Gao
Hong Chang
Danyang Huang
Yingying Ma
...
Ke Xu
Jing Zhou
Xuening Zhu
Yingqiu Zhu
Hansheng Wang
44
7
0
17 Mar 2024
Dual Gauss-Newton Directions for Deep Learning
Dual Gauss-Newton Directions for Deep Learning
Vincent Roulet
Mathieu Blondel
ODL
26
0
0
17 Aug 2023
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model
  Pre-training
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
Hong Liu
Zhiyuan Li
David Leo Wright Hall
Percy Liang
Tengyu Ma
VLM
55
132
0
23 May 2023
Achieving High Accuracy with PINNs via Energy Natural Gradients
Achieving High Accuracy with PINNs via Energy Natural Gradients
Johannes Müller
Marius Zeinhofer
13
5
0
25 Feb 2023
Efficient first-order predictor-corrector multiple objective
  optimization for fair misinformation detection
Efficient first-order predictor-corrector multiple objective optimization for fair misinformation detection
Eric Enouen
Katja Mathesius
Sean Wang
Arielle K. Carr
Sihong Xie
20
2
0
15 Sep 2022
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method
  with Probabilistic Gradient Estimation
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
Matilde Gargiani
Andrea Zanelli
Andrea Martinelli
Tyler H. Summers
John Lygeros
33
14
0
01 Feb 2022
Inexact bilevel stochastic gradient methods for constrained and
  unconstrained lower-level problems
Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems
Tommaso Giovannelli
G. Kent
Luis Nunes Vicente
33
12
0
01 Oct 2021
ViViT: Curvature access through the generalized Gauss-Newton's low-rank
  structure
ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure
Felix Dangel
Lukas Tatzel
Philipp Hennig
29
12
0
04 Jun 2021
1