7 citations · 7 across the 4 of their papers we have counts for
4 papers
Relax and Merge: A Simple Yet Effective Framework for Solving Fair -Means and -sparse Wasserstein Barycenter Problems
Shihong Song, Guanlin Mo, Qingyuan Yang +1
The fairness of clustering algorithms has gained widespread attention across various areas, including machine learning, In this paper, we study fair -means clustering in Euclide…
Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms
Guanlin Mo, Shihong Song, Hu Ding
DBSCAN is a popular density-based clustering algorithm that has many different applications in practice. However, the running time of DBSCAN in high-dimensional space or general me…
Approximate Algorithms For -Sparse Wasserstein Barycenter With Outliers
Qingyuan Yang, Hu Ding
Wasserstein Barycenter (WB) is one of the most fundamental optimization problems in optimal transportation. Given a set of distributions, the goal of WB is to find a new distributi…
On Metric DBSCAN with Low Doubling Dimension
Hu Ding, Fan Yang
The density based clustering method {\em Density-Based Spatial Clustering of Applications with Noise (DBSCAN)} is a popular method for outlier recognition and has received tremendo…