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1805.08095
Cited By
Small steps and giant leaps: Minimal Newton solvers for Deep Learning
21 May 2018
João F. Henriques
Sébastien Ehrhardt
Samuel Albanie
Andrea Vedaldi
ODL
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Papers citing
"Small steps and giant leaps: Minimal Newton solvers for Deep Learning"
13 / 13 papers shown
Gradient Descent with Provably Tuned Learning-rate Schedules
Dravyansh Sharma
227
0
0
04 Dec 2025
Dual Gauss-Newton Directions for Deep Learning
Vincent Roulet
Mathieu Blondel
ODL
218
0
0
17 Aug 2023
FOSI: Hybrid First and Second Order Optimization
International Conference on Learning Representations (ICLR), 2023
Hadar Sivan
Moshe Gabel
Assaf Schuster
ODL
435
2
0
16 Feb 2023
Statistical and Computational Guarantees for Influence Diagnostics
Jillian R. Fisher
Lang Liu
Krishna Pillutla
Y. Choi
Zaïd Harchaoui
TDI
284
0
0
08 Dec 2022
A Stochastic Bundle Method for Interpolating Networks
Alasdair Paren
Leonard Berrada
Rudra P. K. Poudel
M. P. Kumar
248
6
0
29 Jan 2022
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity
A. Davtyan
Sepehr Sameni
L. Cerkezi
Givi Meishvili
Adam Bielski
Paolo Favaro
ODL
464
5
0
07 Jul 2021
AutoSimulate: (Quickly) Learning Synthetic Data Generation
Harkirat Singh Behl
A. G. Baydin
Ran Gal
Juil Sock
Vibhav Vineet
311
25
0
16 Aug 2020
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M. Schmidt
Frank Schneider
Philipp Hennig
ODL
916
195
0
03 Jul 2020
Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods
Minghan Yang
Dong Xu
Yongfeng Li
Zaiwen Wen
Mengyun Chen
ODL
238
3
0
17 Jun 2020
Sketchy Empirical Natural Gradient Methods for Deep Learning
Minghan Yang
Dong Xu
Zaiwen Wen
Mengyun Chen
Pengxiang Xu
302
15
0
10 Jun 2020
Deep Neural Network Learning with Second-Order Optimizers -- a Practical Study with a Stochastic Quasi-Gauss-Newton Method
C. Thiele
Mauricio Araya-Polo
D. Hohl
ODL
217
2
0
06 Apr 2020
Training Neural Networks for and by Interpolation
International Conference on Machine Learning (ICML), 2019
Leonard Berrada
Andrew Zisserman
M. P. Kumar
3DH
271
71
0
13 Jun 2019
An Adaptive Remote Stochastic Gradient Method for Training Neural Networks
Yushu Chen
Hao Jing
Wenlai Zhao
Zhiqiang Liu
Haohuan Fu
Lián Qiao
Wei Xue
Guangwen Yang
ODL
620
2
0
04 May 2019
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