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…
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…
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…