Self-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe
arXiv:2609.25728v1 Announce Type: cross Abstract: Self-supervised learning for combinatorial optimization has emerged as a promising paradigm for solving discrete optimization problems with neural networks, but a central challenge remains: handling hard combinatorial constraints within continuous…