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HyCO: A Hybrid Neural Solver for Combinatorial Optimization
Sequential reinforcement learning (RL) solvers and global diffusion model (DM) solvers for neural combinatorial optimization exhibit complementary failure modes under an optimization-regret view. The former enjoys small marginal regret in the early construction stage, but suffers from horizon-wise compounding errors with super-linear regret growth; the latter avoids horizon compounding but incurs linear or sublinear regret w.r.t. the dimension of the remaining unsolved subspace. We propose Hybrid Neural Solver for Combinatorial Optimization (HyCO), a hybrid inference algorithm that constructs
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-07T21:11:09.000Z
First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.