Gradient-based Hyperparameter Optimization through Reversible Learning

11 February 2015

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

50 / 498 papers shown

Title
A Globally Convergent Gradient-based Bilevel Hyperparameter Optimization Method Ankur Sinha Satender Gunwal Shivam Kumar 20 2 0 25 Aug 2022
Convolutional Ensembling based Few-Shot Defect Detection Technique Soumyajit Karmakar Abeer Banerjee P. Gidde Sumeet Saurav S. Singh UQCV 34 2 0 05 Aug 2022
Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions Sheheryar Mehmood Peter Ochs 42 3 0 05 Aug 2022
Improving Meta-Learning Generalization with Activation-Based Early-Stopping Simon Guiroy C. Pal Gonçalo Mordido Sarath Chandar 40 3 0 03 Aug 2022
Theseus: A Library for Differentiable Nonlinear Optimization Luis Pineda Taosha Fan Maurizio Monge S. Venkataraman Paloma Sodhi ... Austin S. Wang Stuart Anderson Jing Dong Brandon Amos Mustafa Mukadam 39 76 0 19 Jul 2022
Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods Davoud Ataee Tarzanagh Parvin Nazari Bojian Hou Li Shen Laura Balzano 53 10 0 06 Jul 2022
Betty: An Automatic Differentiation Library for Multilevel Optimization Sang Keun Choe Willie Neiswanger P. Xie Eric P. Xing AI4CE 36 30 0 05 Jul 2022
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem Ruichen Jiang Nazanin Abolfazli Aryan Mokhtari Erfan Yazdandoost Hamedani 43 21 0 17 Jun 2022
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation Sebastian Ament Carla P. Gomes 26 8 0 16 Jun 2022
Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification Xueliang Wang Jianyu Cai Shuiwang Ji Houqiang Li Feng Wu Jie Wang 16 0 0 16 Jun 2022
Communication-Efficient Robust Federated Learning with Noisy Labels Junyi Li Jian Pei Heng Huang FedML 34 18 0 11 Jun 2022
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems R. Haider Anuradha M. Annaswamy 31 2 0 11 Jun 2022
Flexible Differentiable Optimization via Model Transformations Mathieu Besançon J. Garcia B. Legat Akshay Sharma 34 9 0 10 Jun 2022
Infinite Recommendation Networks: A Data-Centric Approach Noveen Sachdeva Mehak Preet Dhaliwal Carole-Jean Wu Julian McAuley DD 50 28 0 03 Jun 2022
Dataset Distillation using Neural Feature Regression Yongchao Zhou E. Nezhadarya Jimmy Ba DD FedML 58 153 0 01 Jun 2022
RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model Hangzhi Guo Feiran Jia Jinghui Chen Anna Squicciarini A. Yadav OOD 36 7 0 01 Jun 2022
On the complexity of nonsmooth automatic differentiation Jérôme Bolte Ryan Boustany Edouard Pauwels B. Pesquet-Popescu 26 2 0 01 Jun 2022
Dataset Condensation via Efficient Synthetic-Data Parameterization Jang-Hyun Kim Jinuk Kim Seong Joon Oh Sangdoo Yun Hwanjun Song Joonhyun Jeong Jung-Woo Ha Hyun Oh Song DD 410 162 0 30 May 2022
Will Bilevel Optimizers Benefit from Loops Kaiyi Ji Mingrui Liu Yingbin Liang Lei Ying 45 41 0 27 May 2022
Automated Dynamic Algorithm Configuration Steven Adriaensen André Biedenkapp Gresa Shala Noor H. Awad Theresa Eimer Marius Lindauer Frank Hutter 36 37 0 27 May 2022
DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain Medical Images Hongzheng Yang Cheng Chen Meirui Jiang Quande Liu Jianfeng Cao Pheng Ann Heng Qi Dou OOD 40 26 0 27 May 2022
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning Jiahui Gao Renjie Pi Yong Lin Hang Xu Jiacheng Ye Zhiyong Wu Weizhong Zhang Xiaodan Liang Zhenguo Li Lingpeng Kong SyDa VLM 75 45 0 25 May 2022
Hyper-Learning for Gradient-Based Batch Size Adaptation Calum MacLellan Feng Dong 19 0 0 17 May 2022
Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization Nir Shlezinger Yonina C. Eldar Stephen P. Boyd 48 130 0 05 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 31 7 0 05 May 2022
FedNest: Federated Bilevel, Minimax, and Compositional Optimization Davoud Ataee Tarzanagh Mingchen Li Christos Thrampoulidis Samet Oymak FedML 46 73 0 04 May 2022
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning Antonio Emanuele Cinà Kathrin Grosse Ambra Demontis Sebastiano Vascon Werner Zellinger Bernhard A. Moser Alina Oprea Battista Biggio Marcello Pelillo Fabio Roli AAML 27 119 0 04 May 2022
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction Junyi Li Feihu Huang Heng-Chiao Huang FedML 28 27 0 03 May 2022
Designing Perceptual Puzzles by Differentiating Probabilistic Programs Kartik Chandra Tzu-Mao Li J. Tenenbaum Jonathan Ragan-Kelley AAML 24 21 0 26 Apr 2022
Neuronal diversity can improve machine learning for physics and beyond A. Choudhary Anil Radhakrishnan J. Lindner S. Sinha W. Ditto AI4CE 24 3 0 09 Apr 2022
Equivariance Discovery by Learned Parameter-Sharing Raymond A. Yeh Yuan-Ting Hu M. Hasegawa-Johnson Alex Schwing FedML 37 15 0 07 Apr 2022
Model Based Meta Learning of Critics for Policy Gradients Sarah Bechtle Ludovic Righetti Franziska Meier OffRL 32 0 0 05 Apr 2022
Learning to Accelerate by the Methods of Step-size Planning Hengshuai Yao 24 0 0 01 Apr 2022
Learning the Effect of Registration Hyperparameters with HyperMorph Andrew Hoopes Malte Hoffmann Douglas N. Greve Bruce Fischl John Guttag Adrian Dalca 35 39 0 30 Mar 2022
A Fast and Convergent Proximal Algorithm for Regularized Nonconvex and Nonsmooth Bi-level Optimization Ziyi Chen B. Kailkhura Yi Zhou 26 8 0 30 Mar 2022
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 87 368 0 22 Mar 2022
Practical tradeoffs between memory, compute, and performance in learned optimizers Luke Metz C. Freeman James Harrison Niru Maheswaranathan Jascha Narain Sohl-Dickstein 43 32 0 22 Mar 2022
Learning to Generate Synthetic Training Data using Gradient Matching and Implicit Differentiation Dmitry Medvedev A. Dýakonov DD 22 9 0 16 Mar 2022
Neural Simulated Annealing Alvaro H. C. Correia Daniel E. Worrall Roberto Bondesan 19 7 0 04 Mar 2022
Continuous-Time Meta-Learning with Forward Mode Differentiation T. Deleu David Kanaa Leo Feng Giancarlo Kerg Yoshua Bengio Guillaume Lajoie Pierre-Luc Bacon 31 18 0 02 Mar 2022
Adaptive Gradient Methods with Local Guarantees Zhou Lu Wenhan Xia Sanjeev Arora Elad Hazan ODL 29 9 0 02 Mar 2022
A Primal-Dual Approach to Bilevel Optimization with Multiple Inner Minima Daouda Sow Kaiyi Ji Ziwei Guan Yingbin Liang 37 9 0 01 Mar 2022
Amortized Proximal Optimization Juhan Bae Paul Vicol Jeff Z. HaoChen Roger C. Grosse ODL 36 14 0 28 Feb 2022
The Art of Manipulation: Threat of Multi-Step Manipulative Attacks in Security Games T. Nguyen Arunesh Sinha AAML 17 0 0 27 Feb 2022
Myriad: a real-world testbed to bridge trajectory optimization and deep learning Nikolaus H. R. Howe Simon Dufort-Labbé Nitarshan Rajkumar Pierre-Luc Bacon 32 5 0 22 Feb 2022
Supervising the Multi-Fidelity Race of Hyperparameter Configurations Martin Wistuba Arlind Kadra Josif Grabocka 38 14 0 20 Feb 2022
Teaching Networks to Solve Optimization Problems Xinran Liu Yuzhe Lu Ali Abbasi Meiyi Li Javad Mohammadi Soheil Kolouri 54 11 0 08 Feb 2022
Efficiently Escaping Saddle Points in Bilevel Optimization Minhui Huang Xuxing Chen Kaiyi Ji Shiqian Ma Lifeng Lai 34 21 0 08 Feb 2022
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-start Riccardo Grazzi Massimiliano Pontil Saverio Salzo 33 12 0 07 Feb 2022
Adaptive Mixing of Auxiliary Losses in Supervised Learning D. Sivasubramanian Ayush Maheshwari Pradeep Shenoy A. Prathosh Ganesh Ramakrishnan 29 5 0 07 Feb 2022