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20202026
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cs.DS2026

Improved Learning with Structure: Fine-Grained Complexity of Minimum Consistent Subset

Robert Ganian, Manolis Vasilakis, Simon Wietheger

Instance selection is a vital technique for mitigating the computational bottlenecks of nearest-neighbor classification in large-scale supervised clustering. A classical theoretica…

cs.DS2026

Clustering Permutations under the Ulam Metric: A Parameterized Complexity Study

Tian Bai, Fedor V. Fomin, Petr A. Golovach +2

Rank aggregation seeks a representative permutation for a collection of rankings and plays a central role in areas such as social choice, information retrieval, and computational b…

cs.DS2026

Fair Correlation Clustering Meets Graph Parameters

Johannes Blaha, Robert Ganian, Katharina Gillig +2

We study the generalization of Correlation Clustering which incorporates fairness constraints via the notion of fairlets. The corresponding Fair Correlation Clustering problem has…

cs.DS2025

Matrix Editing Meets Fair Clustering: Parameterized Algorithms and Complexity

Robert Ganian, Hung P. Hoang, Simon Wietheger

We study the computational problem of computing a fair means clustering of discrete vectors, which admits an equivalent formulation as editing a colored matrix into one with few di…

cs.DS2020

A Strategic Routing Framework and Algorithms for Computing Alternative Paths

Thomas Bläsius, Maximilian Böther, Philipp Fischbeck +9

Traditional navigation services find the fastest route for a single driver. Though always using the fastest route seems desirable for every individual, selfish behavior can have un…