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Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems

1 October 2021

Papers citing "Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems"

29 / 29 papers shown

Title
On Penalty-based Bilevel Gradient Descent Method Han Shen Quan-Wu Xiao Tianyi Chen 112 59 0 08 Jan 2025
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation Jeongyeol Kwon Dohyun Kwon Steve Wright Robert D. Nowak 73 30 0 04 Sep 2023
Gradient-based Bi-level Optimization for Deep Learning: A Survey Can Chen Xiangshan Chen Chen Ma Zixuan Liu Xue Liu 176 39 0 24 Jul 2022
Generalized Data Weighting via Class-level Gradient Manipulation Can Chen Shuhao Zheng Xi Chen Erqun Dong Xue Liu Hao Liu Dejing Dou 85 24 0 29 Oct 2021
On the Convergence Theory for Hessian-Free Bilevel Algorithms Daouda Sow Kaiyi Ji Yingbin Liang 85 28 0 13 Oct 2021
Provably Faster Algorithms for Bilevel Optimization Junjie Yang Kaiyi Ji Yingbin Liang 100 136 0 08 Jun 2021
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective Haoran Sun Wenqiang Pu Xiao Fu Tsung-Hui Chang Mingyi Hong 71 30 0 03 May 2021
Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes Sara Sangalli Ertunc Erdil A. Hoetker O. Donati E. Konukoglu AI4CE 63 28 0 21 Feb 2021
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond Risheng Liu Jiaxin Gao Jin Zhang Deyu Meng Zhouchen Lin AI4CE 143 229 0 27 Jan 2021
Bilevel Optimization: Convergence Analysis and Enhanced Design Kaiyi Ji Junjie Yang Yingbin Liang 217 261 0 15 Oct 2020
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization Sauptik Dhar Unmesh Kurup Mohak Shah 74 2 0 27 Jul 2020
On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs Matilde Gargiani Andrea Zanelli Moritz Diehl Frank Hutter ODL 66 18 0 03 Jun 2020
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions Pengzhen Ren Yun Xiao Xiaojun Chang Po-Yao (Bernie) Huang Zhihui Li Xiaojiang Chen Xin Wang AI4CE 127 677 0 01 Jun 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 398 1,988 0 11 Apr 2020
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 130 416 0 06 Nov 2019
The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning Suyun Liu Luis Nunes Vicente 147 75 0 10 Jul 2019
Learning to Defend by Learning to Attack Haoming Jiang Zhehui Chen Yuyang Shi Bo Dai T. Zhao 80 22 0 03 Nov 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 206 4,375 0 24 Jun 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
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong 210 505 0 27 Oct 2017
Gradient Episodic Memory for Continual Learning David Lopez-Paz MarcÁurelio Ranzato VLM CLL 131 2,743 0 26 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
Practical Gauss-Newton Optimisation for Deep Learning Aleksandar Botev H. Ritter David Barber ODL 76 232 0 12 Jun 2017
A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications Ankur Sinha P. Malo Kalyanmoy Deb 48 760 0 17 May 2017
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 254 3,226 0 15 Jun 2016
Hyperparameter optimization with approximate gradient Fabian Pedregosa 130 450 0 07 Feb 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,129 0 20 Dec 2014
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks Ian Goodfellow M. Berk Mirza Xia Da Aaron Courville Yoshua Bengio 159 1,455 0 21 Dec 2013
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 289 14,968 1 21 Dec 2013