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Learning to Optimize: A Primer and A Benchmark

Learning to Optimize: A Primer and A Benchmark

23 March 2021
Tianlong Chen
Xiaohan Chen
Wuyang Chen
Howard Heaton
Jialin Liu
Zhangyang Wang
W. Yin
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Papers citing "Learning to Optimize: A Primer and A Benchmark"

30 / 30 papers shown
Title
Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows
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
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
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
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning
Long Zhou
Fereshteh Shakeri
Aymen Sadraoui
Mounir Kaaniche
J. Pesquet
Ismail Ben Ayed
VLM
75
0
0
21 Dec 2024
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
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
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
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
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
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
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
What's in a Prior? Learned Proximal Networks for Inverse Problems
Zhenghan Fang
Sam Buchanan
Jeremias Sulam
15
11
0
22 Oct 2023
Improving physics-informed neural networks with meta-learned
  optimization
Improving physics-informed neural networks with meta-learned optimization
Alexander Bihlo
PINN
13
18
0
13 Mar 2023
SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements
SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements
Ying Zhang
Zhiqiang Zhao
Zhuo Feng
22
2
0
09 Feb 2023
Optimization for Amortized Inverse Problems
Optimization for Amortized Inverse Problems
Tianci Liu
Tong Yang
Quan Zhang
Qi Lei
11
4
0
25 Oct 2022
On Representing Linear Programs by Graph Neural Networks
On Representing Linear Programs by Graph Neural Networks
Ziang Chen
Jialin Liu
Xinshang Wang
Jian Lu
W. Yin
AI4CE
39
31
0
25 Sep 2022
Self-Supervised Primal-Dual Learning for Constrained Optimization
Self-Supervised Primal-Dual Learning for Constrained Optimization
Seonho Park
Pascal Van Hentenryck
17
45
0
18 Aug 2022
Fixed-Point Automatic Differentiation of Forward--Backward Splitting
  Algorithms for Partly Smooth Functions
Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions
Sheheryar Mehmood
Peter Ochs
22
3
0
05 Aug 2022
Landscape Learning for Neural Network Inversion
Landscape Learning for Neural Network Inversion
Ruoshi Liu
Chen-Guang Mao
Purva Tendulkar
Hongya Wang
Carl Vondrick
11
8
0
17 Jun 2022
Optimization-Derived Learning with Essential Convergence Analysis of
  Training and Hyper-training
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
Automated Dynamic Algorithm Configuration
Steven Adriaensen
André Biedenkapp
Gresa Shala
Noor H. Awad
Theresa Eimer
Marius Lindauer
Frank Hutter
21
36
0
27 May 2022
Expert-Calibrated Learning for Online Optimization with Switching Costs
Expert-Calibrated Learning for Online Optimization with Switching Costs
Pengfei Li
Jianyi Yang
Shaolei Ren
11
11
0
18 Apr 2022
Teaching Networks to Solve Optimization Problems
Teaching Networks to Solve Optimization Problems
Xinran Liu
Yuzhe Lu
Ali Abbasi
Meiyi Li
Javad Mohammadi
Soheil Kolouri
14
11
0
08 Feb 2022
Tutorial on amortized optimization
Tutorial on amortized optimization
Brandon Amos
OffRL
53
42
0
01 Feb 2022
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and
  Applications
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications
Khaled B. Letaief
Yuanming Shi
Jianmin Lu
Jianhua Lu
15
414
0
24 Nov 2021
Iterative Amortized Policy Optimization
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
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction
Yunmei Chen
Hongcheng Liu
X. Ye
Qingchao Zhang
39
21
0
22 Jul 2020
L$^2$-GCN: Layer-Wise and Learned Efficient Training of Graph
  Convolutional Networks
L2^22-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks
Yuning You
Tianlong Chen
Zhangyang Wang
Yang Shen
GNN
86
76
0
30 Mar 2020
The large learning rate phase of deep learning: the catapult mechanism
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
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction
Zhong-Qiu Wang
Jonathan Le Roux
DeLiang Wang
J. Hershey
76
122
0
26 Apr 2018
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
V. Papyan
Yaniv Romano
Michael Elad
48
283
0
27 Jul 2016
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