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Xiao-Liang Wu

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Conference Open access Sep 2026

Parameterized Approximation Schemes for Fair Clustering in Doubling Metrics

Fair clustering has garnered considerable attention, with various fairness notions proposed to ensure equitable representation across demographic groups. In this paper, we focus on the k-center problem in bounded doubling metrics under two popular fairness requirements: group fairness and data summarization fairness, r...

Xiao-Liang Wu, Ting Liang, Zhize Li et al. · 0 citations
2025

A Single-Swap Local Search Algorithm for k-Means of Lines

Clustering is a fundamental problem that has been extensively studied over past few decades, with most research focusing on point-based clustering such as k - means, k -median, and k -center. However, numerous real-world applications, such as motion analysis, computer vision, and missing data analysis, require clusteri...

Ting Liang, Xiao-Liang Wu, Junyu Huang et al. · 0 citations

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