3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
Adaptive and Robust DBSCAN with Multi-agent Reinforcement Learning
Hao Peng, Xiang Huang, Shuo Sun +2
DBSCAN, a well-known density-based clustering algorithm, has gained widespread popularity and usage due to its effectiveness in identifying clusters of arbitrary shapes and handlin…
cs.LG2022★ 3 cited
Automating DBSCAN via Deep Reinforcement Learning
Ruitong Zhang, Hao Peng, Yingtong Dou +4
DBSCAN is widely used in many scientific and engineering fields because of its simplicity and practicality. However, due to its high sensitivity parameters, the accuracy of the clu…