collaborators

5 papers

math.OC2026

Coordinate-wise Polyhedral Method for Eliciting Multivariate Linear Utility and Univariate Nonlinear Utility Functions

Jiaxin Wei, Jia Liu, Huifu Xu

In this paper, we propose a coordinate-wise polyhedral method (CPM) for cutting polyhedra with theoretical guarantees of convergence. Unlike the existing polyhedral method, which d…

math.OC2026

Maximum Utility Split Method for Utility Preference Elicitation

Bo Chen, Jia Liu, Huifu Xu

In this paper, we propose a new approach, called maximum utility split (MUS) scheme, which is built on random utility split (RUS) scheme but with a notable difference: one lottery…

cs.DM2026

A Scalable Lift-and-Project Differentiable Approach For the Maximum Cut Problem

Ismail Alkhouri, Mian Wu, Cunxi Yu +3

We propose a scalable framework for solving the Maximum Cut (MaxCut) problem in large graphs using projected gradient ascent on quadratic objectives. Our approach is differentiable…

cs.NI2025

Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimization

Myeung Suk Oh, Zhiyao Zhang, FNU Hairi +2

With wireless devices increasingly forming a unified smart network for seamless, user-friendly operations, random access (RA) medium access control (MAC) design is considered a key…

cs.DM2025

Differentiable Quadratic Optimization For The Maximum Independent Set Problem

Ismail Alkhouri, Cedric Le Denmat, Yingjie Li +4

Combinatorial Optimization (CO) addresses many important problems, including the challenging Maximum Independent Set (MIS) problem. Alongside exact and heuristic solvers, different…