Parameterized approximation algorithms and lower bounds for \(k\)-center clustering and variants
From MaRDI portal
Publication:6586660
DOI10.1007/S00453-024-01236-1MaRDI QIDQ6586660
Ramin Mousavi, Zachary Friggstad, Sayan Bandyapadhyay
Publication date: 13 August 2024
Published in: Algorithmica (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- The planar \(k\)-means problem is NP-hard
- Clustering to minimize the maximum intercluster distance
- Exact and approximation algorithms for clustering
- Which problems have strongly exponential complexity?
- Reductions among high dimensional proximity problems
- Geometric clustering
- On the Complexity of Some Common Geometric Location Problems
- Extensions of Lipschitz mappings into a Hilbert space
- Linear-time approximation schemes for clustering problems in any dimensions
- Approximate clustering via core-sets
- On coresets for k-means and k-median clustering
- Approximation schemes for clustering problems
- Exponential Time Complexity of the Permanent and the Tutte Polynomial
- A framework for ETH-tight algorithms and lower bounds in geometric intersection graphs
- Parameterized Algorithms
- The Non-Uniform k -Center Problem
- Kernelization for Maximum Leaf Spanning Tree with Positive Vertex Weights
- Tight lower bounds for approximate \& exact \(k\)-center in \(\mathbb{R}^d\)
- Johnson coverage hypothesis: inapproximability of \(k\)-means and \(k\)-median in \(\ell_p\)-metrics
This page was built for publication: Parameterized approximation algorithms and lower bounds for \(k\)-center clustering and variants
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6586660)