Search Results for author: Ragesh Jaiswal

Found 6 papers, 0 papers with code

A Quantum Approximation Scheme for k-Means

no code implementations16 Aug 2023 Ragesh Jaiswal

We give a quantum approximation scheme (i. e., $(1 + \varepsilon)$-approximation for every $\varepsilon > 0$) for the classical $k$-means clustering problem in the QRAM model with a running time that has only polylogarithmic dependence on the number of data points.

Universal Weak Coreset

no code implementations26 May 2023 Ragesh Jaiswal, Amit Kumar

Coresets for $k$-means and $k$-median problems yield a small summary of the data, which preserve the clustering cost with respect to any set of $k$ centers.

Constrained Clustering Data Compression

Tight FPT Approximation for Constrained k-Center and k-Supplier

no code implementations27 Oct 2021 Dishant Goyal, Ragesh Jaiswal

In this work, we study a range of constrained versions of the $k$-supplier and $k$-center problems such as: capacitated, fault-tolerant, fair, etc.

Constrained Clustering

Tight FPT Approximation for Socially Fair Clustering

no code implementations12 Jun 2021 Dishant Goyal, Ragesh Jaiswal

The goal in the socially fair $k$-median problem is to find a set $C \subseteq F$ of $k$ centers that minimizes the maximum average cost over all the groups.

Clustering

Hardness of Approximation of Euclidean $k$-Median

no code implementations9 Nov 2020 Anup Bhattacharya, Dishant Goyal, Ragesh Jaiswal

In this setting, we show the first hardness of approximation result for the Euclidean $k$-median problem for any $\beta < 1. 015$, assuming UGC.

Streaming k-means approximation

no code implementations NeurIPS 2009 Nir Ailon, Ragesh Jaiswal, Claire Monteleoni

We provide a clustering algorithm that approximately optimizes the k-means objective, in the one-pass streaming setting.

Clustering

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