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Scaling Laws for Hyperparameter Optimization

Scaling Laws for Hyperparameter Optimization

1 February 2023
Arlind Kadra
Maciej Janowski
Martin Wistuba
Josif Grabocka
ArXivPDFHTML

Papers citing "Scaling Laws for Hyperparameter Optimization"

12 / 12 papers shown
Title
Position: A Call to Action for a Human-Centered AutoML Paradigm
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer
Florian Karl
A. Klier
Julia Moosbauer
Alexander Tornede
Andreas Mueller
Frank Hutter
Matthias Feurer
Bernd Bischl
41
6
0
05 Jun 2024
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of
  Learning Curve Extrapolation
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation
Dong Bok Lee
Aoxuan Silvia Zhang
Byung-Hoon Kim
Junhyeon Park
Juho Lee
Sung Ju Hwang
Haebeom Lee
34
1
0
28 May 2024
Reshuffling Resampling Splits Can Improve Generalization of
  Hyperparameter Optimization
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
Thomas Nagler
Lennart Schneider
B. Bischl
Matthias Feurer
45
2
0
24 May 2024
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango
Fabio Ferreira
Arlind Kadra
Frank Hutter
Frank Hutter Josif Grabocka
37
15
0
06 Jun 2023
Deep Ranking Ensembles for Hyperparameter Optimization
Deep Ranking Ensembles for Hyperparameter Optimization
Abdus Salam Khazi
Sebastian Pineda Arango
Josif Grabocka
BDL
39
7
0
27 Mar 2023
Optimizing Data Collection for Machine Learning
Optimizing Data Collection for Machine Learning
Rafid Mahmood
James Lucas
J. Álvarez
Sanja Fidler
M. Law
93
26
0
03 Oct 2022
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter
  Optimization
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Marius Lindauer
Katharina Eggensperger
Matthias Feurer
André Biedenkapp
Difan Deng
C. Benjamins
Tim Ruhopf
René Sass
Frank Hutter
85
328
0
20 Sep 2021
Provably Efficient Online Hyperparameter Optimization with
  Population-Based Bandits
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
Jack Parker-Holder
Vu Nguyen
Stephen J. Roberts
OffRL
75
83
0
06 Feb 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
264
4,489
0
23 Jan 2020
Forward and Reverse Gradient-Based Hyperparameter Optimization
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi
Michele Donini
P. Frasconi
Massimiliano Pontil
133
409
0
06 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
297
10,225
0
16 Nov 2016
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