Learning to Optimize: A Primer and A Benchmark

23 March 2021

Papers citing "Learning to Optimize: A Primer and A Benchmark"

47 / 47 papers shown

Title
Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows Wenhao Li Bo Jin Mingyi Hong Changhong Lu Xiangfeng Wang 48 0 0 07 May 2025
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers Elad Sofer Tomer Shaked Caroline Chaux Nir Shlezinger AAML 45 0 0 26 Apr 2025
Verification and Validation for Trustworthy Scientific Machine Learning John D. Jakeman Lorena A. Barba J. Martins Thomas O'Leary-Roseberry AI4CE 56 0 0 21 Feb 2025
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning Long Zhou Fereshteh Shakeri Aymen Sadraoui Mounir Kaaniche J. Pesquet Ismail Ben Ayed VLM 84 0 0 21 Dec 2024
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery Renpu Liu Ruida Zhou Cong Shen Jing Yang 25 0 0 17 Oct 2024
Self-Supervised Learning of Iterative Solvers for Constrained Optimization Lukas Luken Sergio Lucia 29 0 0 12 Sep 2024
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic Xi Zhang Brandon Amos Mathieu Blanchette Leo J. Lee Yoshua Bengio Alexander Tong Kirill Neklyudov 33 5 0 26 Aug 2024
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning Frederik Hoppe C. M. Verdun Hannah Laus Felix Krahmer Holger Rauhut UQCV 22 1 0 18 Jul 2024
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure Can Pouliquen Mathurin Massias Titouan Vayer 38 0 0 13 Jun 2024
From Learning to Optimize to Learning Optimization Algorithms Camille Castera Peter Ochs 59 1 0 28 May 2024
Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be? Jorge F. Urbán P. Stefanou José A. Pons PINN 43 6 0 07 May 2024
ILILT: Implicit Learning of Inverse Lithography Technologies Haoyu Yang Haoxing Ren 33 3 0 06 May 2024
From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto S. Wasserkrug Léonard Boussioux D. Hertog F. Mirzazadeh Ilker Birbil Jannis Kurtz Donato Maragno LLMAG 32 3 0 26 Feb 2024
What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang Sam Buchanan Jeremias Sulam 31 11 0 22 Oct 2023
Improving physics-informed neural networks with meta-learned optimization Alexander Bihlo PINN 31 18 0 13 Mar 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning Adam X. Yang Laurence Aitchison Henry B. Moss 29 4 0 22 Feb 2023
SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements Ying Zhang Zhiqiang Zhao Zhuo Feng 38 2 0 09 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 31 9 0 02 Feb 2023
A Nonstochastic Control Approach to Optimization Xinyi Chen Elad Hazan 47 5 0 19 Jan 2023
Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints Jianyi Yang Shaolei Ren 18 2 0 03 Dec 2022
Solving 3D Radar Imaging Inverse Problems with a Multi-cognition Task-oriented Framework Xu Zhan Xiaoling Zhang Mou Wang Jun Shi Shunjun Wei Tianjiao Zeng 21 1 0 28 Nov 2022
Optimization for Amortized Inverse Problems Tianci Liu Tong Yang Quan Zhang Qi Lei 26 4 0 25 Oct 2022
Learning Variational Models with Unrolling and Bilevel Optimization Christoph Brauer Niklas Breustedt T. Wolff D. Lorenz SSL 29 3 0 26 Sep 2022
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 57 31 0 25 Sep 2022
Estimating a potential without the agony of the partition function E. Haber Moshe Eliasof L. Tenorio 25 2 0 19 Aug 2022
Self-Supervised Primal-Dual Learning for Constrained Optimization Seonho Park Pascal Van Hentenryck 25 46 0 18 Aug 2022
Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions Sheheryar Mehmood Peter Ochs 33 3 0 05 Aug 2022
Landscape Learning for Neural Network Inversion Ruoshi Liu Chen-Guang Mao Purva Tendulkar Hongya Wang Carl Vondrick 32 8 0 17 Jun 2022
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training Risheng Liu Xuan Liu Shangzhi Zeng Jin Zhang Yixuan Zhang 35 6 0 16 Jun 2022
Automated Dynamic Algorithm Configuration Steven Adriaensen André Biedenkapp Gresa Shala Noor H. Awad Theresa Eimer Marius Lindauer Frank Hutter 27 36 0 27 May 2022
Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization Nir Shlezinger Yonina C. Eldar Stephen P. Boyd 22 130 0 05 May 2022
Explainable AI via Learning to Optimize Howard Heaton Samy Wu Fung 24 14 0 29 Apr 2022
Expert-Calibrated Learning for Online Optimization with Switching Costs Pengfei Li Jianyi Yang Shaolei Ren 24 11 0 18 Apr 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 37 18 0 13 Mar 2022
Teaching Networks to Solve Optimization Problems Xinran Liu Yuzhe Lu Ali Abbasi Meiyi Li Javad Mohammadi Soheil Kolouri 36 11 0 08 Feb 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Learning for Robust Combinatorial Optimization: Algorithm and Application Zhihui Shao Jianyi Yang Cong Shen Shaolei Ren 30 6 0 20 Dec 2021
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications Khaled B. Letaief Yuanming Shi Jianmin Lu Jianhua Lu 32 416 0 24 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks Maksym Yatsura J. H. Metzen Matthias Hein OOD 24 14 0 02 Nov 2021
Hyperparameter Tuning is All You Need for LISTA Xiaohan Chen Jialin Liu Zhangyang Wang W. Yin ODL 30 23 0 29 Oct 2021
Iterative Amortized Policy Optimization Joseph Marino Alexandre Piché Alessandro Davide Ialongo Yisong Yue OffRL 54 22 0 20 Oct 2020
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction Yunmei Chen Hongcheng Liu X. Ye Qingchao Zhang 50 23 0 22 Jul 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
The large learning rate phase of deep learning: the catapult mechanism Aitor Lewkowycz Yasaman Bahri Ethan Dyer Jascha Narain Sohl-Dickstein Guy Gur-Ari ODL 159 234 0 04 Mar 2020
Safeguarded Learned Convex Optimization Howard Heaton Xiaohan Chen Zhangyang Wang W. Yin 18 22 0 04 Mar 2020
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction Zhong-Qiu Wang Jonathan Le Roux DeLiang Wang J. Hershey 88 123 0 26 Apr 2018
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding V. Papyan Yaniv Romano Michael Elad 56 284 0 27 Jul 2016