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Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians
  Clustering
v1v2 (latest)

Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering

8 November 2018
K. Makarychev
Kaizhu Huang
Jeyarajan Thiyagalingam
ArXiv (abs)PDFHTML

Papers citing "Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering"

50 / 66 papers shown
Title
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao
Rajesh Jayaram
Benedikt Kolbe
Shay Sapir
Chris Schwiegelshohn
Sandeep Silwal
Erik Waingarten
15
0
0
30 May 2025
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Sandeep Silwal
David P. Woodruff
Qiuyi Zhang
100
0
0
27 Feb 2025
A Tight VC-Dimension Analysis of Clustering Coresets with Applications
A Tight VC-Dimension Analysis of Clustering Coresets with Applications
Vincent Cohen-Addad
Andrew Draganov
Matteo Russo
David Saulpic
Chris Schwiegelshohn
66
2
0
11 Jan 2025
Making Old Things New: A Unified Algorithm for Differentially Private
  Clustering
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupré la Tour
Monika Henzinger
David Saulpic
FedML
65
2
0
17 Jun 2024
Contrastive Explainable Clustering with Differential Privacy
Contrastive Explainable Clustering with Differential Privacy
Dung Nguyen
Ariel Vetzler
Sarit Kraus
A. Vullikanti
74
1
0
07 Jun 2024
Coresets for Multiple $\ell_p$ Regression
Coresets for Multiple ℓp\ell_pℓp​ Regression
David P. Woodruff
T. Yasuda
52
0
0
04 Jun 2024
Approximate Algorithms For $k$-Sparse Wasserstein Barycenter With
  Outliers
Approximate Algorithms For kkk-Sparse Wasserstein Barycenter With Outliers
Qingyuan Yang
Hu Ding
55
3
0
20 Apr 2024
Node Similarities under Random Projections: Limits and Pathological
  Cases
Node Similarities under Random Projections: Limits and Pathological Cases
Tvrtko Tadić
Cassiano Becker
Jennifer Neville
96
0
0
15 Apr 2024
Settling Time vs. Accuracy Tradeoffs for Clustering Big Data
Settling Time vs. Accuracy Tradeoffs for Clustering Big Data
Andrew Draganov
David Saulpic
Chris Schwiegelshohn
47
5
0
02 Apr 2024
Efficiently Computing Similarities to Private Datasets
Efficiently Computing Similarities to Private Datasets
A. Backurs
Zinan Lin
S. Mahabadi
Sandeep Silwal
Jakub Tarnawski
88
6
0
13 Mar 2024
A Scalable Algorithm for Individually Fair K-means Clustering
A Scalable Algorithm for Individually Fair K-means Clustering
M. Bateni
Vincent Cohen-Addad
Alessandro Epasto
Silvio Lattanzi
91
7
0
09 Feb 2024
On Robust Wasserstein Barycenter: The Model and Algorithm
On Robust Wasserstein Barycenter: The Model and Algorithm
Xu Wang
Jiawei Huang
Qing Yang
Jinpeng Zhang
50
1
0
25 Dec 2023
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile
  Streaming
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
Gregory Dexter
P. Drineas
David P. Woodruff
T. Yasuda
35
0
0
29 Oct 2023
Simple, Scalable and Effective Clustering via One-Dimensional
  Projections
Simple, Scalable and Effective Clustering via One-Dimensional Projections
Moses Charikar
Monika Henzinger
Lunjia Hu
Maximilian Vötsch
Erik Waingarten
65
2
0
25 Oct 2023
Fast and Simple Spectral Clustering in Theory and Practice
Fast and Simple Spectral Clustering in Theory and Practice
Peter Macgregor
80
6
0
17 Oct 2023
On Generalization Bounds for Projective Clustering
On Generalization Bounds for Projective Clustering
Maria Sofia Bucarelli
Matilde Fjeldso Larsen
Chris Schwiegelshohn
M. Toftrup
46
3
0
13 Oct 2023
Differential Privacy for Clustering Under Continual Observation
Differential Privacy for Clustering Under Continual Observation
Max Dupré la Tour
Monika Henzinger
David Saulpic
50
1
0
07 Jul 2023
Adversarially robust clustering with optimality guarantees
Adversarially robust clustering with optimality guarantees
Soham Jana
Kun Yang
Sanjeev R. Kulkarni
AAML
51
2
0
16 Jun 2023
Approximation Algorithms for Fair Range Clustering
Approximation Algorithms for Fair Range Clustering
S. S. Hotegni
S. Mahabadi
A. Vakilian
57
19
0
11 Jun 2023
Learning the Positions in CountSketch
Learning the Positions in CountSketch
Yi Li
Honghao Lin
Simin Liu
A. Vakilian
David P. Woodruff
84
19
0
11 Jun 2023
Randomly Projected Convex Clustering Model: Motivation, Realization, and
  Cluster Recovery Guarantees
Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees
Ziwen Wang
Yancheng Yuan
Jiaming Ma
T. Zeng
Defeng Sun
32
3
0
29 Mar 2023
Exact Non-Oblivious Performance of Rademacher Random Embeddings
Exact Non-Oblivious Performance of Rademacher Random Embeddings
Maciej Skorski
Alessandro Temperoni
112
0
0
21 Mar 2023
Replicable Clustering
Replicable Clustering
Hossein Esfandiari
Amin Karbasi
Vahab Mirrokni
Grigoris Velegkas
Felix Y. Zhou
91
13
0
20 Feb 2023
Feature Affinity Assisted Knowledge Distillation and Quantization of
  Deep Neural Networks on Label-Free Data
Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data
Zhijian Li
Biao Yang
Penghang Yin
Y. Qi
Jack Xin
MQ
30
2
0
10 Feb 2023
Cheeger Inequalities for Directed Graphs and Hypergraphs Using
  Reweighted Eigenvalues
Cheeger Inequalities for Directed Graphs and Hypergraphs Using Reweighted Eigenvalues
L. Lau
Kam Chuen Tung
Robert Wang
81
7
0
17 Nov 2022
On The Relative Error of Random Fourier Features for Preserving Kernel
  Distance
On The Relative Error of Random Fourier Features for Preserving Kernel Distance
Kuan Cheng
S. Jiang
Luojian Wei
Zhide Wei
86
1
0
01 Oct 2022
Socially Fair Center-based and Linear Subspace Clustering
Socially Fair Center-based and Linear Subspace Clustering
Sruthi Gorantla
Kishen N. Gowda
Amit Deshpande
Anand Louis
65
2
0
22 Aug 2022
An Empirical Evaluation of $k$-Means Coresets
An Empirical Evaluation of kkk-Means Coresets
Chris Schwiegelshohn
Omar Ali Sheikh-Omar
39
11
0
03 Jul 2022
$k$-Median Clustering via Metric Embedding: Towards Better
  Initialization with Differential Privacy
kkk-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy
Chenglin Fan
Ping Li
Xiaoyun Li
83
6
0
26 Jun 2022
Scalable Differentially Private Clustering via Hierarchically Separated
  Trees
Scalable Differentially Private Clustering via Hierarchically Separated Trees
Vincent Cohen-Addad
Alessandro Epasto
Silvio Lattanzi
Vahab Mirrokni
Andrés Muñoz
David Saulpic
Chris Schwiegelshohn
Sergei Vassilvitskii
FedML
56
16
0
17 Jun 2022
Hashing Learning with Hyper-Class Representation
Hashing Learning with Hyper-Class Representation
Shi-bo Zhang
Jiaye Li
62
1
0
06 Jun 2022
Improved Approximations for Euclidean $k$-means and $k$-median, via
  Nested Quasi-Independent Sets
Improved Approximations for Euclidean kkk-means and kkk-median, via Nested Quasi-Independent Sets
Vincent Cohen-Addad
Hossein Esfandiari
Vahab Mirrokni
Shyam Narayanan
95
37
0
11 Apr 2022
Towards Optimal Lower Bounds for k-median and k-means Coresets
Towards Optimal Lower Bounds for k-median and k-means Coresets
Vincent Cohen-Addad
Kasper Green Larsen
David Saulpic
Chris Schwiegelshohn
56
51
0
25 Feb 2022
Robust and Provable Guarantees for Sparse Random Embeddings
Robust and Provable Guarantees for Sparse Random Embeddings
Maciej Skorski
Alessandro Temperoni
Martin Theobald
86
2
0
22 Feb 2022
Explainable k-means. Don't be greedy, plant bigger trees!
Explainable k-means. Don't be greedy, plant bigger trees!
K. Makarychev
Liren Shan
52
23
0
04 Nov 2021
Learning-Augmented $k$-means Clustering
Learning-Augmented kkk-means Clustering
Jon Ergun
Zhili Feng
Sandeep Silwal
David P. Woodruff
Samson Zhou
67
34
0
27 Oct 2021
Dimensionality Reduction for Wasserstein Barycenter
Dimensionality Reduction for Wasserstein Barycenter
Zachary Izzo
Sandeep Silwal
Samson Zhou
71
18
0
18 Oct 2021
Probabilistic methods for approximate archetypal analysis
Probabilistic methods for approximate archetypal analysis
Ruijian Han
Braxton Osting
Dong Wang
Yiming Xu
49
6
0
12 Aug 2021
Randomized Dimensionality Reduction for Facility Location and
  Single-Linkage Clustering
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
Shyam Narayanan
Sandeep Silwal
Piotr Indyk
Or Zamir
37
12
0
05 Jul 2021
Near-optimal Algorithms for Explainable k-Medians and k-Means
Near-optimal Algorithms for Explainable k-Medians and k-Means
K. Makarychev
Liren Shan
53
27
0
02 Jul 2021
Near-Optimal Explainable $k$-Means for All Dimensions
Near-Optimal Explainable kkk-Means for All Dimensions
Moses Charikar
Lunjia Hu
57
18
0
29 Jun 2021
Locally Private $k$-Means Clustering with Constant Multiplicative
  Approximation and Near-Optimal Additive Error
Locally Private kkk-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error
Anamay Chaturvedi
Matthew D. Jones
Huy Le Nguyen
21
4
0
31 May 2021
Locally Private k-Means in One Round
Locally Private k-Means in One Round
Alisa Chang
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
91
32
0
20 Apr 2021
Confidence-Optimal Random Embeddings
Confidence-Optimal Random Embeddings
Maciej Skorski
14
0
0
06 Apr 2021
Approximation Algorithms for Socially Fair Clustering
Approximation Algorithms for Socially Fair Clustering
Yury Makarychev
A. Vakilian
78
50
0
03 Mar 2021
An Introduction to Johnson-Lindenstrauss Transforms
An Introduction to Johnson-Lindenstrauss Transforms
Casper Benjamin Freksen
8
17
0
28 Feb 2021
Communication-efficient k-Means for Edge-based Machine Learning
Communication-efficient k-Means for Edge-based Machine Learning
Hanlin Lu
T. He
Shiqiang Wang
Changchang Liu
M. Mahdavi
V. Narayanan
Kevin S. Chan
Stephen Pasteris
42
0
0
08 Feb 2021
Fast and Accurate $k$-means++ via Rejection Sampling
Fast and Accurate kkk-means++ via Rejection Sampling
Vincent Cohen-Addad
Silvio Lattanzi
A. Norouzi-Fard
C. Sohler
O. Svensson
VLM
63
20
0
22 Dec 2020
Hardness of Approximation of Euclidean $k$-Median
Hardness of Approximation of Euclidean kkk-Median
Anup Bhattacharya
Dishant Goyal
Ragesh Jaiswal
34
9
0
09 Nov 2020
Improved Guarantees for k-means++ and k-means++ Parallel
Improved Guarantees for k-means++ and k-means++ Parallel
K. Makarychev
Aravind Reddy
Liren Shan
DRL
80
24
0
27 Oct 2020
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