3 citations · 4 across the 4 of their papers we have counts for
7 papers
Monte Carlo Tree Search based Space Transfer for Black-box Optimization
Shukuan Wang, Ke Xue, Lei Song +2
Bayesian optimization (BO) is a popular method for computationally expensive black-box optimization. However, traditional BO methods need to solve new problems from scratch, leadin…
Offline Multi-Objective Optimization
Ke Xue, Rong-Xi Tan, Xiaobin Huang +1
Offline optimization aims to maximize a black-box objective function with a static dataset and has wide applications. In addition to the objective function being black-box and expe…
Quality-Diversity Algorithms Can Provably Be Helpful for Optimization
Chao Qian, Ke Xue, Ren-Jian Wang
Quality-Diversity (QD) algorithms are a new type of Evolutionary Algorithms (EAs), aiming to find a set of high-performing, yet diverse solutions. They have found many successful a…
Fast Teammate Adaptation in the Presence of Sudden Policy Change
Ziqian Zhang, Lei Yuan, Lihe Li +5
In cooperative multi-agent reinforcement learning (MARL), where an agent coordinates with teammate(s) for a shared goal, it may sustain non-stationary caused by the policy change o…
Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackers
Lei Yuan, Zi-Qian Zhang, Ke Xue +6
Cooperative multi-agent reinforcement learning (CMARL) has shown to be promising for many real-world applications. Previous works mainly focus on improving coordination ability via…
Flow by Gauss curvature to the -Gaussian Minkowski problem
Weimin Sheng, Ke Xue
In this paper, we study the -Gaussian Minkowski problem, which arises in the -Brunn-Minkowski theory in Gaussian probability space. We use Aleksandrov's variational metho…