3 papers
cs.LG2026
CADO: From Imitation to Cost Minimization for Heatmap-based Solvers in Combinatorial Optimization
Hyungseok Song, Deunsol Yoon, Kanghoon Lee +3
Heatmap-based solvers have emerged as a promising paradigm for Combinatorial Optimization (CO). However, we argue that the dominant Supervised Learning (SL) training paradigm suffe…
cs.LG2025
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
Jeonghye Kim, Yongjae Shin, Whiyoung Jung +5
Reinforcement learning with offline data suffers from Q-value extrapolation errors. To address this issue, we first demonstrate that linear extrapolation of the Q-function beyond t…
cs.AI2025
Unsupervised Training of Diffusion Models for Feasible Solution Generation in Neural Combinatorial Optimization
Seong-Hyun Hong, Hyun-Sung Kim, Zian Jang +3
Recent advancements in neural combinatorial optimization (NCO) methods have shown promising results in generating near-optimal solutions without the need for expert-crafted heurist…