10 citations · 33 across the 24 of their papers we have counts for
7 papers · 1 filter
Parameterized Approximation Algorithms for -Center Clustering and Variants
Sayan Bandyapadhyay, Zachary Friggstad, Ramin Mousavi
-center is one of the most popular clustering models. While it admits a simple 2-approximation in polynomial time in general metrics, the Euclidean version is NP-hard to approxi…
How to Find a Good Explanation for Clustering?
Sayan Bandyapadhyay, Fedor V. Fomin, Petr A. Golovach +3
-means and -median clustering are powerful unsupervised machine learning techniques. However, due to complicated dependences on all the features, it is challenging to interpr…
Subexponential Parameterized Algorithms for Cut and Cycle Hitting Problems on H-Minor-Free Graphs
Sayan Bandyapadhyay, William Lochet, Daniel Lokshtanov +2
We design the first subexponential-time (parameterized) algorithms for several cut and cycle-hitting problems on -minor free graphs. In particular, we obtain the following resul…
Exact and Approximation Algorithms for Many-To-Many Point Matching in the Plane
Sayan Bandyapadhyay, Anil Maheshwari, Michiel Smid
Given two sets and of points in the plane, of total size , a {many-to-many} matching between and is a set of pairs such that , and for e…
FPT Approximation for Fair Minimum-Load Clustering
Sayan Bandyapadhyay, Fedor V. Fomin, Petr A. Golovach +2
In this paper, we consider the Minimum-Load -Clustering/Facility Location (MLkC) problem where we are given a set of points in a metric space that we have to cluster and…
Lossy Kernelization of Same-Size Clustering
Sayan Bandyapadhyay, Fedor V. Fomin, Petr A. Golovach +2
In this work, we study the -median clustering problem with an additional equal-size constraint on the clusters, from the perspective of parameterized preprocessing. Our main res…
Parameterized Complexity of Feature Selection for Categorical Data Clustering
Sayan Bandyapadhyay, Fedor V. Fomin, Petr A. Golovach +1
We develop new algorithmic methods with provable guarantees for feature selection in regard to categorical data clustering. While feature selection is one of the most common approa…