Optimizing Millions of Hyperparameters by Implicit Differentiation

6 November 2019

Paul Vicol

Papers citing "Optimizing Millions of Hyperparameters by Implicit Differentiation"

21 / 271 papers shown

Title
Gradient-based Hyperparameter Optimization Over Long Horizons P. Micaelli Amos Storkey 16 15 0 15 Jul 2020
Meta-Learning Symmetries by Reparameterization Allan Zhou Tom Knowles Chelsea Finn OOD 24 91 0 06 Jul 2020
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Zhongzheng Ren Raymond A. Yeh Alex Schwing 38 95 0 02 Jul 2020
On the Iteration Complexity of Hypergradient Computation Riccardo Grazzi Luca Franceschi Massimiliano Pontil Saverio Salzo 50 193 0 29 Jun 2020
Auxiliary Learning by Implicit Differentiation Aviv Navon Idan Achituve Haggai Maron Gal Chechik Ethan Fetaya 33 59 0 22 Jun 2020
Flexible Dataset Distillation: Learn Labels Instead of Images Ondrej Bohdal Yongxin Yang Timothy M. Hospedales DD 35 110 0 15 Jun 2020
Meta Approach to Data Augmentation Optimization Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 32 34 0 14 Jun 2020
Multi-step Estimation for Gradient-based Meta-learning Jin-Hwa Kim Junyoung Park Yongseok Choi 22 1 0 08 Jun 2020
Learning Convex Optimization Models Akshay Agrawal Shane T. Barratt Stephen P. Boyd 36 40 0 07 Jun 2020
Coresets via Bilevel Optimization for Continual Learning and Streaming Zalan Borsos Mojmír Mutný Andreas Krause CLL 38 227 0 06 Jun 2020
AutoHAS: Efficient Hyperparameter and Architecture Search Xuanyi Dong Mingxing Tan Adams Wei Yu Daiyi Peng Bogdan Gabrys Quoc V. Le TPM 19 23 0 05 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 34 7 0 05 Jun 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 93 1,935 0 11 Apr 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization Quentin Bertrand Quentin Klopfenstein Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon 30 64 0 20 Feb 2020
Penalty Method for Inversion-Free Deep Bilevel Optimization Akshay Mehra Jihun Hamm 24 46 0 08 Nov 2019
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach Yuanhao Wang Guodong Zhang Jimmy Ba 33 100 0 16 Oct 2019
Modular Meta-Learning with Shrinkage Yutian Chen A. Friesen Feryal M. P. Behbahani Arnaud Doucet David Budden Matthew W. Hoffman Nando de Freitas KELM OffRL 23 35 0 12 Sep 2019
Automated Machine Learning: From Principles to Practices Quanming Yao Mengshuo Wang Hugo Jair Escalante Huan Zhao Qiang Yang 25 258 0 31 Oct 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 112 718 0 13 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 463 11,715 0 09 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 133 409 0 06 Mar 2017