Jinxiang Gan

collaborators

2 papers

cs.DC2023

Fair $k$ -Center: a Coreset Approach in Low Dimensions

Jinxiang Gan, Mordecai Golin, Zonghan Yang +1

Center-based clustering techniques are fundamental in some areas of machine learning such as data summarization. Generic $k$ -center algorithms can produce biased cluster representa…

cs.DS2023

Fully Dynamic $k$ -Center in Low Dimensions via Approximate Furthest Neighbors

Jinxiang Gan, Mordecai Jay Golin

Let $P$ be a set of points in some metric space. The approximate furthest neighbor problem is, given a second point set $C,$ to find a point $p \in P$ that is a $(1 + ε)$ approximate…

Fair k-Center: a Coreset Approach in Low Dimensions

Fully Dynamic k-Center in Low Dimensions via Approximate Furthest Neighbors

Fair $k$ -Center: a Coreset Approach in Low Dimensions

Fully Dynamic $k$ -Center in Low Dimensions via Approximate Furthest Neighbors