Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

Papers citing "Gradient-based Hyperparameter Optimization through Reversible Learning"

50 / 497 papers shown

Title
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty Jaehoon Oh Sungnyun Kim Namgyu Ho Jin-Hwa Kim Hwanjun Song Se-Young Yun 30 34 0 01 Feb 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression Giacomo Meanti Luigi Carratino E. De Vito Lorenzo Rosasco 24 12 0 17 Jan 2022
Discrete Simulation Optimization for Tuning Machine Learning Method Hyperparameters V. Ramamohan Shobhit Singhal Aditya Gupta N. Bolia 16 1 0 16 Jan 2022
When less is more: Simplifying inputs aids neural network understanding R. Schirrmeister Rosanne Liu Sara Hooker T. Ball 24 5 0 14 Jan 2022
Automated Reinforcement Learning: An Overview Reza Refaei Afshar Yingqian Zhang Joaquin Vanschoren U. Kaymak OffRL 36 16 0 13 Jan 2022
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation Wendi Li Xiao Yang Weiqing Liu Yingce Xia Jiang Bian DiffM AI4TS 28 51 0 11 Jan 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 19 67 0 04 Jan 2022
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies Paul Vicol Luke Metz Jascha Narain Sohl-Dickstein 27 67 0 27 Dec 2021
Lyapunov Exponents for Diversity in Differentiable Games Jonathan Lorraine Paul Vicol Jack Parker-Holder Tal Kachman Luke Metz Jakob N. Foerster 35 7 0 24 Dec 2021
Automated Deep Learning: Neural Architecture Search Is Not the End Xuanyi Dong D. Kedziora Katarzyna Musial Bogdan Gabrys 25 26 0 16 Dec 2021
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse Junyi Li Bin Gu Heng-Chiao Huang 26 72 0 09 Dec 2021
Hyper-parameter optimization based on soft actor critic and hierarchical mixture regularization Chaoyue Liu Yulai Zhang 13 0 0 08 Dec 2021
Predicting the success of Gradient Descent for a particular Dataset-Architecture-Initialization (DAI) Umang Jain H. G. Ramaswamy AI4CE 13 1 0 25 Nov 2021
DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing Taesik Gong Yewon Kim Adiba Orzikulova Yunxin Liu Sung Ju Hwang Jinwoo Shin Sung-Ju Lee 22 8 0 22 Nov 2021
CONFAIR: Configurable and Interpretable Algorithmic Fairness Ankit Kulshrestha Ilya Safro FaML 22 2 0 17 Nov 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 30 93 0 10 Nov 2021
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 63 69 0 09 Nov 2021
Meta-Learning to Improve Pre-Training Aniruddh Raghu Jonathan Lorraine Simon Kornblith Matthew B. A. McDermott David Duvenaud 24 30 0 02 Nov 2021
Learning where to learn: Gradient sparsity in meta and continual learning J. Oswald Dominic Zhao Seijin Kobayashi Simon Schug Massimo Caccia Nicolas Zucchet João Sacramento CLL 17 46 0 27 Oct 2021
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation Ross M. Clarke E. T. Oldewage José Miguel Hernández-Lobato 28 9 0 20 Oct 2021
Differentiable Rendering with Perturbed Optimizers Quentin Le Lidec Ivan Laptev Cordelia Schmid Justin Carpentier 24 15 0 18 Oct 2021
On the Convergence Theory for Hessian-Free Bilevel Algorithms Daouda Sow Kaiyi Ji Yingbin Liang 28 28 0 13 Oct 2021
Which Samples Should be Learned First: Easy or Hard? Xiaoling Zhou Ou Wu 26 17 0 11 Oct 2021
Value-Function-based Sequential Minimization for Bi-level Optimization Risheng Liu Xuan Liu Shangzhi Zeng Jin Zhang Yixuan Zhang 40 30 0 11 Oct 2021
Online Hyperparameter Meta-Learning with Hypergradient Distillation Haebeom Lee Hayeon Lee Jaewoong Shin Eunho Yang Timothy M. Hospedales Sung Ju Hwang DD 39 2 0 06 Oct 2021
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games Shinsaku Sakaue Kengo Nakamura 14 3 0 05 Oct 2021
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu Jiayang Li Zhuoran Yang Hoi-To Wai Mingyi Hong Y. Nie Zhaoran Wang 66 18 0 04 Oct 2021
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond Risheng Liu Yaohua Liu Shangzhi Zeng Jin Zhang 24 80 0 01 Oct 2021
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO Katharina Eggensperger Philip Muller Neeratyoy Mallik Matthias Feurer René Sass Aaron Klein Noor H. Awad Marius Lindauer Frank Hutter 46 100 0 14 Sep 2021
DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture Kaichen Zhou Lanqing Hong Shuailiang Hu Fengwei Zhou Binxin Ru Jiashi Feng Zhenguo Li 62 10 0 13 Sep 2021
Bootstrapped Meta-Learning Sebastian Flennerhag Yannick Schroecker Tom Zahavy Hado van Hasselt David Silver Satinder Singh 38 59 0 09 Sep 2021
Normal Learning in Videos with Attention Prototype Network Chao Hu Fan Wu Weijie Wu Weibin Qiu Shengxin Lai 17 1 0 25 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 36 5 0 12 Aug 2021
Modular Meta-Learning for Power Control via Random Edge Graph Neural Networks I. Nikoloska Osvaldo Simeone 33 22 0 04 Aug 2021
Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization K. Cohen Sangwoo Park Osvaldo Simeone S. Shamai 23 12 0 02 Aug 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang Kyle Hsu Jianing Li Chelsea Finn Roger C. Grosse 11 39 0 21 Jul 2021
Soft Layer Selection with Meta-Learning for Zero-Shot Cross-Lingual Transfer Weijia Xu Batool Haider Jason Krone Saab Mansour 23 7 0 21 Jul 2021
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression William T. Stephenson Zachary Frangella Madeleine Udell Tamara Broderick 22 12 0 19 Jul 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 85 448 0 13 Jul 2021
iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients Miao Zhang Steven W. Su Shirui Pan Xiaojun Chang Ehsan Abbasnejad Reza Haffari 24 68 0 21 Jun 2021
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization Ondrej Bohdal Yongxin Yang Timothy M. Hospedales 20 20 0 19 Jun 2021
Graph Contrastive Learning Automated Yuning You Tianlong Chen Yang Shen Zhangyang Wang 24 447 0 10 Jun 2021
Provably Faster Algorithms for Bilevel Optimization Junjie Yang Kaiyi Ji Yingbin Liang 49 132 0 08 Jun 2021
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization Fan Bao Guoqiang Wu Chongxuan Li Jun Zhu Bo Zhang 30 30 0 08 Jun 2021
Shifting Transformation Learning for Out-of-Distribution Detection Sina Mohseni Arash Vahdat J. Yadawa OODD 30 7 0 07 Jun 2021
Debiasing a First-order Heuristic for Approximate Bi-level Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller AI4CE 19 5 0 04 Jun 2021
A Generalizable Approach to Learning Optimizers Diogo Almeida Clemens Winter Jie Tang Wojciech Zaremba AI4CE 19 29 0 02 Jun 2021
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent Anis Elgabli Chaouki Ben Issaid Amrit Singh Bedi M. Bennis Vaneet Aggarwal FedML 21 4 0 31 May 2021
Training With Data Dependent Dynamic Learning Rates Shreyas Saxena Nidhi Vyas D. DeCoste ODL 6 1 0 27 May 2021