Copertina

On Size and Hardness Generalization in Unsupervised Learning for the Travelling Salesman Problem

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Min, Yimeng, Gomes, Carla P.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unsupervised Learning for Solving the Travelling Salesman Problem
di: Min, Yimeng, et al.
Pubblicazione: (2023)

Unsupervised Learning for Quadratic Assignment
di: Min, Yimeng, et al.
Pubblicazione: (2025)

Structure As Search: Unsupervised Permutation Learning for Combinatorial Optimization
di: Min, Yimeng, et al.
Pubblicazione: (2025)

Comment on paper: Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
di: Min, Yimeng
Pubblicazione: (2024)

Learning Unbiased Permutations via Flow Matching
di: Min, Yimeng, et al.
Pubblicazione: (2026)

Looking Ahead to Avoid Being Late: Solving Hard-Constrained Traveling Salesman Problem
di: Chen, Jingxiao, et al.
Pubblicazione: (2024)

Generative Modeling for Robust Deep Reinforcement Learning on the Traveling Salesman Problem
di: Li, Michael, et al.
Pubblicazione: (2025)

Distilling Privileged Information for Dubins Traveling Salesman Problems with Neighborhoods
di: Shin, Min Kyu, et al.
Pubblicazione: (2024)

Divergence-Suppressing Couplings for Rectified Flow
di: Min, Yimeng, et al.
Pubblicazione: (2026)

Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
di: Li, Qi, et al.
Pubblicazione: (2025)

Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem
di: Goh, Yong Liang, et al.
Pubblicazione: (2022)

A Unified Deep Reinforcement Learning Approach for Close Enough Traveling Salesman Problem
di: Fan, Mingfeng, et al.
Pubblicazione: (2025)

An End-to-End Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drones
di: Zeng, Taihelong, et al.
Pubblicazione: (2025)

Adaptation and Fine-tuning with TabPFN for Travelling Salesman Problem
di: Vu, Nguyen Gia Hien, et al.
Pubblicazione: (2025)

Construct, Merge, Solve & Adapt with Reinforcement Learning for the min-max Multiple Traveling Salesman Problem
di: Rodríguez-Corominas, Guillem, et al.
Pubblicazione: (2026)

iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning
di: Guo, Yifan, et al.
Pubblicazione: (2024)

Permutation Picture of Graph Combinatorial Optimization Problems
di: Min, Yimeng
Pubblicazione: (2024)

Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
di: Xia, Yifan, et al.
Pubblicazione: (2024)

Unsupervised Ordering for Maximum Clique
di: Min, Yimeng, et al.
Pubblicazione: (2025)

HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
di: Cotnareanu, Joseph, et al.
Pubblicazione: (2024)

Graph Neural Networks are Heuristics
di: Min, Yimeng, et al.
Pubblicazione: (2026)

Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem
di: Strauß, Niklas, et al.
Pubblicazione: (2024)

Deep Reinforcement Learning for Traveling Purchaser Problems
di: Yuan, Haofeng, et al.
Pubblicazione: (2024)

Test-Time Augmentation for Traveling Salesperson Problem
di: Ishiyama, Ryo, et al.
Pubblicazione: (2024)

HardNet: Hard-Constrained Neural Networks with Universal Approximation Guarantees
di: Min, Youngjae, et al.
Pubblicazione: (2024)

A First Guess is Rarely the Final Answer: Learning to Search in the Traveling Salesperson Problem
di: Garmendia, Andoni Irazusta
Pubblicazione: (2026)

An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem
di: Liu, Huaiyuan, et al.
Pubblicazione: (2024)

Verifier-Backed Hard Problem Generation for Mathematical Reasoning
di: Lai, Yuhang, et al.
Pubblicazione: (2026)

Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection
di: Zhang, Ruyi, et al.
Pubblicazione: (2024)

Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman Problems
di: Xiao, Yubin, et al.
Pubblicazione: (2023)

Bandit based Dynamic Candidate Edge Selection in Solving Traveling Salesman Problems
di: Wang, Long, et al.
Pubblicazione: (2025)

HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline
di: Li, Yang, et al.
Pubblicazione: (2023)

Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing
di: Lee, Sewoong, et al.
Pubblicazione: (2023)

Multimodal Fused Learning for Solving the Generalized Traveling Salesman Problem in Robotic Task Planning
di: Cheng, Jiaqi, et al.
Pubblicazione: (2025)

POPE: Learning to Reason on Hard Problems via Privileged On-Policy Exploration
di: Qu, Yuxiao, et al.
Pubblicazione: (2026)

More Consistent Accuracy PINN via Alternating Easy-Hard Training
di: Gao, Zhaoqian, et al.
Pubblicazione: (2025)

Health Index Estimation Through Integration of General Knowledge with Unsupervised Learning
di: Bajarunas, Kristupas, et al.
Pubblicazione: (2024)

Freeze and Conquer: Reusable Ansatz for Solving the Traveling Salesman Problem
di: Fagiolo, Fabrizio, et al.
Pubblicazione: (2025)

Machine Learning for Two-Stage Graph Sparsification for the Travelling Salesman Problem
di: Lin, Bo-Cheng, et al.
Pubblicazione: (2026)

Steiner Traveling Salesman Problem with Quantum Annealing
di: Ciacco, Alessia, et al.
Pubblicazione: (2025)