2 papers
cs.DS2026
Sample-and-Search: An Effective Algorithm for Learning-Augmented k-Median Clustering in High dimensions
Kangke Cheng, Shihong Song, Guanlin Mo +1
In this paper, we investigate the learning-augmented -median clustering problem, which aims to improve the performance of traditional clustering algorithms by preprocessing the…
cs.LG2024
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…