26 citations · 92 across the 15 of their papers we have counts for
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cs.LG2021★ 5 cited
Smart Feasibility Pump: Reinforcement Learning for (Mixed) Integer Programming
Meng Qi, Mengxin Wang, Zuo-Jun Shen
In this work, we propose a deep reinforcement learning (DRL) model for finding a feasible solution for (mixed) integer programming (MIP) problems. Finding a feasible solution for M…
cs.LG2020
Fatigue-aware Bandits for Dependent Click Models
Junyu Cao, Wei Sun, Zuo-Jun +2
As recommender systems send a massive amount of content to keep users engaged, users may experience fatigue which is contributed by 1) an overexposure to irrelevant content, 2) bor…
cs.LG2019★ 4 cited
Adjusting Rate of Spread Factors through Derivative-Free Optimization: A New Methodology to Improve the Performance of Forest Fire Simulators
Jaime Carrasco, Cristobal Pais, Zuo-Jun Max Shen +1
In practical applications, it is common that wildfire simulators do not correctly predict the evolution of the fire scar. Usually, this is caused due to multiple factors including…