10 citations · 40 across the 27 of their papers we have counts for
6 papers · 1 filter
Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation
Xiaobin Huang, Lei Song, Ke Xue +1
Bayesian optimization (BO) is a sample-efficient method and has been widely used for optimizing expensive black-box functions. Recently, there has been a considerable interest in B…
Diversity from Human Feedback
Ren-Jian Wang, Ke Xue, Yutong Wang +4
Diversity plays a significant role in many problems, such as ensemble learning, reinforcement learning, and combinatorial optimization. How to define the diversity measure is a lon…
Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy
Chengrui Gao, Haopu Shang, Ke Xue +2
Machine learning has been adapted to help solve NP-hard combinatorial optimization problems. One prevalent way is learning to construct solutions by deep neural networks, which has…
Macro Placement by Wire-Mask-Guided Black-Box Optimization
Yunqi Shi, Ke Xue, Lei Song +1
The development of very large-scale integration (VLSI) technology has posed new challenges for electronic design automation (EDA) techniques in chip floorplanning. During this proc…
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…