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A Unified Framework for Approximating and Clustering Data

A Unified Framework for Approximating and Clustering Data

7 June 2011
Dan Feldman
M. Langberg
ArXivPDFHTML

Papers citing "A Unified Framework for Approximating and Clustering Data"

6 / 6 papers shown
Title
Geometric Median Matching for Robust k-Subset Selection from Noisy Data
Geometric Median Matching for Robust k-Subset Selection from Noisy Data
Anish Acharya
Sujay Sanghavi
Alexandros G. Dimakis
Inderjit S Dhillon
AAML
115
0
0
01 Apr 2025
Provable Imbalanced Point Clustering
Provable Imbalanced Point Clustering
David Denisov
Dan Feldman
Shlomi Dolev
Michael Segal
96
0
0
13 Mar 2025
Geometric Median (GM) Matching for Robust Data Pruning
Geometric Median (GM) Matching for Robust Data Pruning
Anish Acharya
Inderjit S Dhillon
Sujay Sanghavi
AAML
96
0
0
20 Jan 2025
Diversity-aware clustering: Computational Complexity and Approximation Algorithms
Diversity-aware clustering: Computational Complexity and Approximation Algorithms
Suhas Thejaswi
Ameet Gadekar
Bruno Ordozgoiti
Aristides Gionis
42
2
0
10 Jan 2024
On the Local Structure of Stable Clustering Instances
On the Local Structure of Stable Clustering Instances
Vincent Cohen-Addad
Chris Schwiegelshohn
102
48
0
29 Jan 2017
Optimal Time Bounds for Approximate Clustering
Optimal Time Bounds for Approximate Clustering
Ramgopal R. Mettu
Greg Plaxton
32
118
0
12 Dec 2012
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