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Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

25 October 2019
Prabhu Teja Sivaprasad
Florian Mai
Thijs Vogels
Martin Jaggi
François Fleuret
ArXivPDFHTML

Papers citing "Optimizer Benchmarking Needs to Account for Hyperparameter Tuning"

5 / 5 papers shown
Title
Design-Bench: Benchmarks for Data-Driven Offline Model-Based
  Optimization
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization
Brandon Trabucco
Xinyang Geng
Aviral Kumar
Sergey Levine
OffRL
34
95
0
17 Feb 2022
Tasks, stability, architecture, and compute: Training more effective
  learned optimizers, and using them to train themselves
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves
Luke Metz
Niru Maheswaranathan
C. Freeman
Ben Poole
Jascha Narain Sohl-Dickstein
33
62
0
23 Sep 2020
Descending through a Crowded Valley - Benchmarking Deep Learning
  Optimizers
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M. Schmidt
Frank Schneider
Philipp Hennig
ODL
40
162
0
03 Jul 2020
Optimization for deep learning: theory and algorithms
Optimization for deep learning: theory and algorithms
Ruoyu Sun
ODL
27
168
0
19 Dec 2019
Demon: Improved Neural Network Training with Momentum Decay
Demon: Improved Neural Network Training with Momentum Decay
John Chen
Cameron R. Wolfe
Zhaoqi Li
Anastasios Kyrillidis
ODL
24
15
0
11 Oct 2019
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