Learning to Optimize: A Primer and A Benchmark

23 March 2021

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

24 / 24 papers shown

Title
Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows Wenhao Li Bo Jin Mingyi Hong Changhong Lu Xiangfeng Wang 36 0 0 07 May 2025
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers Elad Sofer Tomer Shaked Caroline Chaux Nir Shlezinger AAML 28 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 72 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 18 0 0 17 Oct 2024
Self-Supervised Learning of Iterative Solvers for Constrained Optimization Lukas Luken Sergio Lucia 13 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 29 5 0 26 Aug 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 26 1 0 28 May 2024
ILILT: Implicit Learning of Inverse Lithography Technologies Haoyu Yang Haoxing Ren 23 3 0 06 May 2024
What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang Sam Buchanan Jeremias Sulam 15 11 0 22 Oct 2023
SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements Ying Zhang Zhiqiang Zhao Zhuo Feng 22 2 0 09 Feb 2023
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 36 31 0 25 Sep 2022
Self-Supervised Primal-Dual Learning for Constrained Optimization Seonho Park Pascal Van Hentenryck 15 45 0 18 Aug 2022
Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions Sheheryar Mehmood Peter Ochs 22 3 0 05 Aug 2022
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training Risheng Liu Xuan Liu Shangzhi Zeng Jin Zhang Yixuan Zhang 14 6 0 16 Jun 2022
Automated Dynamic Algorithm Configuration Steven Adriaensen André Biedenkapp Gresa Shala Noor H. Awad Theresa Eimer Marius Lindauer Frank Hutter 19 36 0 27 May 2022
Tutorial on amortized optimization Brandon Amos OffRL 50 42 0 01 Feb 2022
Iterative Amortized Policy Optimization Joseph Marino Alexandre Piché Alessandro Davide Ialongo Yisong Yue OffRL 42 21 0 20 Oct 2020
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction Yunmei Chen Hongcheng Liu X. Ye Qingchao Zhang 35 21 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 83 76 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 143 198 0 04 Mar 2020
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction Zhong-Qiu Wang Jonathan Le Roux DeLiang Wang J. Hershey 71 122 0 26 Apr 2018
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding V. Papyan Yaniv Romano Michael Elad 48 283 0 27 Jul 2016