Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm

Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm

17 February 2021

Heng-Chiao Huang

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Papers citing "Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm"

18 / 18 papers shown

Title
BOHB: Robust and Efficient Hyperparameter Optimization at Scale Stefan Falkner Aaron Klein Frank Hutter BDL 211 1,102 0 04 Jul 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 102 580 0 04 Jul 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 179 732 0 13 Jun 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 88 531 0 28 May 2018
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 220 417 0 06 Mar 2017
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization Lisha Li Kevin Jamieson Giulia DeSalvo Afshin Rostamizadeh Ameet Talwalkar 240 2,336 0 21 Mar 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 119 604 0 19 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 127 392 0 17 Mar 2016
Hyperparameter optimization with approximate gradient Fabian Pedregosa 130 450 0 07 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,510 0 10 Dec 2015
Gradient-based Hyperparameter Optimization through Reversible Learning D. Maclaurin David Duvenaud Ryan P. Adams DD 234 946 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,529 0 04 Sep 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 137 1,828 0 01 Jul 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 163 741 0 19 Mar 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 122 1,562 0 22 Sep 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 382 7,965 0 13 Jun 2012
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning E. Brochu Vlad M. Cora Nando de Freitas GP 138 2,449 0 12 Dec 2010

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