5 papers
Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
Yancheng Chen, Dun Ma, Shuai Zhang +6
Graph Foundation Models (GFMs), built upon the Pre-training and Adaptation paradigm, have emerged as a research hotspot in graph learning. For GNN-based GFMs, graph prompt tuning h…
Smoothing Binary Optimization: A Primal-Dual Perspective
Wenbo Liu, Akang Wang, Dun Ma +3
Binary optimization is a powerful tool for modeling combinatorial problems, yet scalable and theoretically sound solution methods remain elusive. Conventional solvers often rely on…
Mixed-Integer Linear Optimization via Learning-Based Two-Layer Large Neighborhood Search
Wenbo Liu, Akang Wang, Wenguo Yang +1
Mixed-integer linear programs (MILPs) are extensively used to model practical problems such as planning and scheduling. A prominent method for solving MILPs is large neighborhood s…
Parallel Graver Basis Extraction for Nonlinear Integer Optimization
Wenbo Liu, Akang Wang, Wenguo Yang
The augmentation scheme provides a nontraditional approach to nonlinear integer programming by iteratively refining incumbent solutions along objective-improving directions from th…
On Representing Convex Quadratically Constrained Quadratic Programs via Graph Neural Networks
Chenyang Wu, Qian Chen, Akang Wang +4
Convex quadratically constrained quadratic programs (QCQPs) involve finding a solution within a convex feasible region defined by quadratic constraints while minimizing a convex qu…