15 citations · 20 across the 15 of their papers we have counts for
4 papers · 1 filter
State Sequences Prediction via Fourier Transform for Representation Learning
Mingxuan Ye, Yufei Kuang, Jie Wang +4
While deep reinforcement learning (RL) has been demonstrated effective in solving complex control tasks, sample efficiency remains a key challenge due to the large amounts of data…
Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning
Yufei Kuang, Xijun Li, Jie Wang +7
Large-scale LP problems from industry usually contain much redundancy that severely hurts the efficiency and reliability of solving LPs, making presolve (i.e., the problem simplifi…
Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation
Haoyang Liu, Yufei Kuang, Jie Wang +3
Machine learning has been successfully applied to improve the efficiency of Mixed-Integer Linear Programming (MILP) solvers. However, the learning-based solvers often suffer from s…
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
Zhihai Wang, Xijun Li, Jie Wang +5
Cutting planes (cuts) are important for solving mixed-integer linear programs (MILPs), which formulate a wide range of important real-world applications. Cut selection -- which aim…