Learning to Optimize

6 June 2016

Papers citing "Learning to Optimize"

50 / 54 papers shown

Title
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach Rares Cristian Pavithra Harsha Georgia Perakis Brian Quanz 19 0 0 16 May 2025
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery Renpu Liu Ruida Zhou Cong Shen Jing Yang 37 0 0 17 Oct 2024
Self-Supervised Learning of Iterative Solvers for Constrained Optimization Lukas Luken Sergio Lucia 41 0 0 12 Sep 2024
A New First-Order Meta-Learning Algorithm with Convergence Guarantees El Mahdi Chayti Martin Jaggi 38 1 0 05 Sep 2024
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning Frederik Hoppe C. M. Verdun Hannah Laus Felix Krahmer Holger Rauhut UQCV 36 1 0 18 Jul 2024
Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander David Goldie Chris Xiaoxuan Lu Matthew Jackson Shimon Whiteson Jakob N. Foerster 46 3 0 09 Jul 2024
From Learning to Optimize to Learning Optimization Algorithms Camille Castera Peter Ochs 65 1 0 28 May 2024
A Deep Learning Based Resource Allocator for Communication Systems with Dynamic User Utility Demands Pourya Behmandpoor Panagiotis Patrinos Marc Moonen 30 1 0 08 Nov 2023
Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning Huan Zhang Jinliang Ding Liang Feng Kay Chen Tan Ke Li 45 3 0 19 Oct 2023
Advances and Challenges in Meta-Learning: A Technical Review Anna Vettoruzzo Mohamed-Rafik Bouguelia Joaquin Vanschoren Thorsteinn Rögnvaldsson K. Santosh OffRL 36 70 0 10 Jul 2023
Permutation Equivariant Neural Functionals Allan Zhou Kaien Yang Kaylee Burns Adriano Cardace Yiding Jiang Samuel Sokota J. Zico Kolter Chelsea Finn 40 47 0 27 Feb 2023
Learning to Optimize for Reinforcement Learning Qingfeng Lan Rupam Mahmood Shuicheng Yan Zhongwen Xu OffRL 36 6 0 03 Feb 2023
Mnemosyne: Learning to Train Transformers with Transformers Deepali Jain K. Choromanski Kumar Avinava Dubey Sumeet Singh Vikas Sindhwani Tingnan Zhang Jie Tan OffRL 49 9 0 02 Feb 2023
Thompson Sampling on Asymmetric $α$ -Stable Bandits Zhendong Shi E. Kuruoglu Xiaoli Wei 11 0 0 19 Mar 2022
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning Haoxiang Wang Yite Wang Ruoyu Sun Bo Li 38 27 0 17 Mar 2022
Amortized Proximal Optimization Juhan Bae Paul Vicol Jeff Z. HaoChen Roger C. Grosse ODL 38 14 0 28 Feb 2022
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 85 455 0 13 Jul 2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty Zehao Xiao Jiayi Shen Xiantong Zhen Ling Shao Cees G. M. Snoek BDL UQCV OOD 29 39 0 09 May 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 67 223 0 27 Jan 2021
Training Stronger Baselines for Learning to Optimize Tianlong Chen Weiyi Zhang Jingyang Zhou Shiyu Chang Sijia Liu Lisa Amini Zhangyang Wang OffRL 27 51 0 18 Oct 2020
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves Luke Metz Niru Maheswaranathan C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 37 62 0 23 Sep 2020
L $^2$ -GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks Yuning You Tianlong Chen Zhangyang Wang Yang Shen GNN 101 82 0 30 Mar 2020
Learning to Learn Single Domain Generalization Fengchun Qiao Long Zhao Xi Peng OOD 57 433 0 30 Mar 2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch Esteban Real Chen Liang David R. So Quoc V. Le 44 220 0 06 Mar 2020
Safeguarded Learned Convex Optimization Howard Heaton Xiaohan Chen Zhangyang Wang W. Yin 24 22 0 04 Mar 2020
Learning to Optimize in Swarms Yue Cao Tianlong Chen Zhangyang Wang Yang Shen 25 55 0 09 Nov 2019
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation Risto Vuorio Shao-Hua Sun Hexiang Hu Joseph J. Lim 32 219 0 30 Oct 2019
Domain Generalization via Model-Agnostic Learning of Semantic Features Qi Dou Daniel Coelho De Castro Konstantinos Kamnitsas Ben Glocker OOD 57 686 0 29 Oct 2019
Meta-Learning with Implicit Gradients Aravind Rajeswaran Chelsea Finn Sham Kakade Sergey Levine 51 844 0 10 Sep 2019
Discovery of Useful Questions as Auxiliary Tasks Vivek Veeriah Matteo Hessel Zhongwen Xu Richard L. Lewis Janarthanan Rajendran Junhyuk Oh H. V. Hasselt David Silver Satinder Singh LLMAG 22 86 0 10 Sep 2019
Meta-Learning with Warped Gradient Descent Sebastian Flennerhag Andrei A. Rusu Razvan Pascanu Francesco Visin Hujun Yin R. Hadsell 8 209 0 30 Aug 2019
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters Marius Lindauer Matthias Feurer Katharina Eggensperger André Biedenkapp Frank Hutter 28 18 0 19 Aug 2019
Optimizing quantum heuristics with meta-learning M. Wilson Rachel Stromswold Filip Wudarski Stuart Hadfield N. Tubman E. Rieffel 19 74 0 08 Aug 2019
Learning Surrogate Losses Josif Grabocka Randolf Scholz Lars Schmidt-Thieme 27 41 0 24 May 2019
Meta-learning of Sequential Strategies Pedro A. Ortega Jane X. Wang Mark Rowland Tim Genewein Z. Kurth-Nelson ... Yee Whye Teh H. V. Hasselt Nando de Freitas M. Botvinick Shane Legg OffRL 27 97 0 08 May 2019
Mitigating Metaphors: A Comprehensible Guide to Recent Nature-Inspired Algorithms M. Lones 14 67 0 21 Feb 2019
Deep Unfolding of a Proximal Interior Point Method for Image Restoration Carla Bertocchi Émilie Chouzenoux M. Corbineau J. Pesquet M. Prato 27 107 0 11 Dec 2018
Deep Frank-Wolfe For Neural Network Optimization Leonard Berrada Andrew Zisserman M. P. Kumar ODL 21 40 0 19 Nov 2018
Meta-Learning: A Survey Joaquin Vanschoren FedML OOD 39 756 0 08 Oct 2018
AutoLoss: Learning Discrete Schedules for Alternate Optimization Haowen Xu Huatian Zhang Zhiting Hu Xiaodan Liang Ruslan Salakhutdinov Eric Xing 32 30 0 04 Oct 2018
On the Convergence of Learning-based Iterative Methods for Nonconvex Inverse Problems Risheng Liu Shichao Cheng Yi He Xin-Yue Fan Zhouchen Lin Zhongxuan Luo 29 68 0 16 Aug 2018
Unsupervised Meta-Learning for Reinforcement Learning Abhishek Gupta Benjamin Eysenbach Chelsea Finn Sergey Levine SSL OffRL 54 106 0 12 Jun 2018
The Three Pillars of Machine Programming Justin Emile Gottschlich Armando Solar-Lezama Nesime Tatbul Michael Carbin Martin Rinard Regina Barzilay Saman P. Amarasinghe J. Tenenbaum Tim Mattson 27 62 0 20 Mar 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant Chelsea Finn Sergey Levine Trevor Darrell Thomas Griffiths BDL 26 505 0 26 Jan 2018
Neural Optimizer Search with Reinforcement Learning Irwan Bello Barret Zoph Vijay Vasudevan Quoc V. Le ODL 29 383 0 21 Sep 2017
A Brief Survey of Deep Reinforcement Learning Kai Arulkumaran M. Deisenroth Miles Brundage Anil Anthony Bharath OffRL 65 2,780 0 19 Aug 2017
Learning Combinatorial Optimization Algorithms over Graphs H. Dai Elias Boutros Khalil Yuyu Zhang B. Dilkina Le Song 46 1,446 0 05 Apr 2017
Learning Gradient Descent: Better Generalization and Longer Horizons Kaifeng Lyu Shunhua Jiang Jian Li 20 113 0 10 Mar 2017
Learning to Optimize Neural Nets Ke Li Jitendra Malik 23 130 0 01 Mar 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 106 1,505 0 25 Jan 2017