Author

Sina Azizeddin

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Preprint Oct 2026

Fair Diversity Maximization via Local Search

This work presents a new local-search framework that yields a $4-approximation for any constant number of groups, with no restrictions on the metric space or on the size of the selected set, and is the first constant-factor approximation whose guarantee is independent of the number of groups in this general setting.

Mohammad Ansari, Sina Azizeddin, AmirMohammad Bandari et al. · 0 citations

Preprint Aug 2026

Constrained Correlation Clustering: Towards Optimality

This work identifies Constrained Correlation Clustering as a variant of Correlation Clustering for which optimal approximations might be within reach, and significantly tighten the gap, by showing that the optimal approximation factor lies in $[2,\frac{16}{7}-\gamma)$ for a small constant $0$.

Sina Azizeddin, Evangelos Kipouridis, Nithin M. Varma · 2 citations