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20152026
most citedParameterized Approximation for Robust Clustering in Discrete Geometric Spaces

1 citations · 2 across the 11 of their papers we have counts for

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cs.DS2026

On the Parameterized Approximability of (Mergeable) Sum of Radii Clustering

Ameet Gadekar

The sum of radii problem (-MSR) asks, given a metric space on points, to place balls covering all points so as to minimize the sum of their radii. Despite extensive stud…

cs.DS2026

FPT Approximations for Fair Sum of Radii with Outliers and General Norm Objectives

Ameet Gadekar

The sum of radii problem is a classical clustering problem in which, given a set of points and an integer , the goal is to place balls that cover while minimizing th…

cs.DS2025

Fair Committee Selection under Ordinal Preferences and Limited Cardinal Information

Ameet Gadekar, Aristides Gionis, Suhas Thejaswi +1

We study the problem of fair -committee selection under an egalitarian objective. Given agents partitioned into groups (\eg, demographic quotas), the goal is to aggregat…

cs.DS2025

Label-consistent clustering for evolving data

Ameet Gadekar, Aristides Gionis, Thibault Marette

Data analysis often involves an iterative process, where solutions must be continuously refined in response to new data. Typically, as new data becomes available, an existing solut…

cs.DS2025

Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms

Ameet Gadekar, Suhas Thejaswi

Capacitated fair-range -clustering generalizes classical -clustering by incorporating both capacity constraints and demographic fairness. In this setting, each facility has a…

cs.DS2025

Clustering under Constraints: Efficient Parameterized Approximation Schemes

Sujoy Bhore, Ameet Gadekar, Tanmay Inamdar

We present a unified framework that yields EPASes for constrained -clustering in metric spaces of bounded (algorithmic) scatter dimension, a notion introduced by Abbasi et a…

cs.DS2025

Dimension-Free Parameterized Approximation Schemes for Hybrid Clustering

Ameet Gadekar, Tanmay Inamdar

Hybrid -Clustering is a model of clustering that generalizes two of the most widely studied clustering objectives: -Center and -Median. In this model, given a set of p…

cs.DS2024

FPT approximations for Capacitated Sum of Radii and Diameters

Arnold Filtser, Ameet Gadekar

The Capacitated Sum of Radii problem involves partitioning a set of points , where each point has capacity , into clusters that minimize the sum of cluster rad…

cs.DS2024

Diversity-aware clustering: Computational Complexity and Approximation Algorithms

Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti +1

In this work, we study diversity-aware clustering problems where the data points are associated with multiple attributes resulting in intersecting groups. A clustering solution nee…

cs.DS2023★ 1 cited

Parameterized Approximation for Robust Clustering in Discrete Geometric Spaces

Fateme Abbasi, Sandip Banerjee, Jarosław Byrka +6

We consider the well-studied Robust -Clustering problem, which generalizes the classic -Median, -Means, and -Center problems. Given a constant , the input…

cs.DS2023

Parameterized Approximation Schemes for Clustering with General Norm Objectives

Fateme Abbasi, Sandip Banerjee, Jarosław Byrka +6

This paper considers the well-studied algorithmic regime of designing a -approximation algorithm for a -clustering problem that runs in time (sometimes ca…

cs.DS2021★ 1 cited

Clustering with fair-center representation: parameterized approximation algorithms and heuristics

Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti +1

We study a variant of classical clustering formulations in the context of algorithmic fairness, known as diversity-aware clustering. In this variant we are given a collection of fa…

cs.DS2015

On learning k-parities with and without noise

Arnab Bhattacharyya, Ameet Gadekar, Ninad Rajgopal

We first consider the problem of learning -parities in the on-line mistake-bound model: given a hidden vector with and a sequence of "questions" $a_1,…