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Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning

Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning

8 January 2023
Hao Wang
Pan Li
ArXivPDFHTML

Papers citing "Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning"

10 / 10 papers shown
Title
Regularized Langevin Dynamics for Combinatorial Optimization
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng
Yiming Yang
73
0
0
01 Feb 2025
An Unsupervised Learning Framework Combined with Heuristics for the
  Maximum Minimal Cut Problem
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem
Huaiyuan Liu
Xianzhang Liu
Donghua Yang
Hongzhi Wang
Yingchi Long
Mengtong Ji
Dongjing Miao
Zhiyu Liang
25
0
0
16 Aug 2024
A Diffusion Model Framework for Unsupervised Neural Combinatorial
  Optimization
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
Sebastian Sanokowski
Sepp Hochreiter
Sebastian Lehner
32
17
0
03 Jun 2024
Tackling Prevalent Conditions in Unsupervised Combinatorial
  Optimization: Cardinality, Minimum, Covering, and More
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
Fanchen Bu
Hyeonsoo Jo
Soo Yong Lee
Sungsoo Ahn
Kijung Shin
22
3
0
14 May 2024
Continuous Tensor Relaxation for Finding Diverse Solutions in
  Combinatorial Optimization Problems
Continuous Tensor Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems
Yuma Ichikawa
Hiroaki Iwashita
CLL
21
1
0
03 Feb 2024
Variational Annealing on Graphs for Combinatorial Optimization
Variational Annealing on Graphs for Combinatorial Optimization
Sebastian Sanokowski
Wilhelm Berghammer
Sepp Hochreiter
Sebastian Lehner
56
13
0
23 Nov 2023
Maximum Independent Set: Self-Training through Dynamic Programming
Maximum Independent Set: Self-Training through Dynamic Programming
Lorenzo Brusca
Lars C.P.M. Quaedvlieg
Stratis Skoulakis
Grigorios G. Chrysos
V. Cevher
SSL
27
7
0
28 Oct 2023
Are Graph Neural Networks Optimal Approximation Algorithms?
Are Graph Neural Networks Optimal Approximation Algorithms?
Morris Yau
Eric Lu
Nikolaos Karalias
Jessica Xu
Stefanie Jegelka
26
1
0
01 Oct 2023
Controlling Continuous Relaxation for Combinatorial Optimization
Controlling Continuous Relaxation for Combinatorial Optimization
Yuma Ichikawa
32
4
0
29 Sep 2023
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
362
11,700
0
09 Mar 2017
1