15 citations · 35 across the 6 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.LG2022★ 1 cited
Efficient Exploration in Resource-Restricted Reinforcement Learning
Zhihai Wang, Taoxing Pan, Qi Zhou +1
In many real-world applications of reinforcement learning (RL), performing actions requires consuming certain types of resources that are non-replenishable in each episode. Typical…
math.OC2022★ 3 cited
Learning to Reformulate for Linear Programming
Xijun Li, Qingyu Qu, Fangzhou Zhu +4
It has been verified that the linear programming (LP) is able to formulate many real-life optimization problems, which can obtain the optimum by resorting to corresponding solvers…
cs.LG2022★ 11 cited
An Improved Reinforcement Learning Algorithm for Learning to Branch
Qingyu Qu, Xijun Li, Yunfan Zhou +6
Most combinatorial optimization problems can be formulated as mixed integer linear programming (MILP), in which branch-and-bound (B\&B) is a general and widely used method. Recentl…