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

8 November 2018

K. Makarychev

Kaizhu Huang

Jeyarajan Thiyagalingam

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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 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 Sandeep Silwal David P. Woodruff Qiuyi Zhang 100 0 0 27 Feb 2025
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 Max Dupré la Tour Monika Henzinger David Saulpic FedML 65 2 0 17 Jun 2024
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 $\ell_p$ Regression David P. Woodruff T. Yasuda 52 0 0 04 Jun 2024
Approximate Algorithms For $k$ -Sparse Wasserstein Barycenter With Outliers Qingyuan Yang Hu Ding 55 3 0 20 Apr 2024
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 Andrew Draganov David Saulpic Chris Schwiegelshohn 47 5 0 02 Apr 2024
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 M. Bateni Vincent Cohen-Addad Alessandro Epasto Silvio Lattanzi 91 7 0 09 Feb 2024
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 Gregory Dexter P. Drineas David P. Woodruff T. Yasuda 33 0 0 29 Oct 2023
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 Peter Macgregor 80 6 0 17 Oct 2023
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 Max Dupré la Tour Monika Henzinger David Saulpic 50 1 0 07 Jul 2023
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 S. S. Hotegni S. Mahabadi A. Vakilian 57 19 0 11 Jun 2023
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 Ziwen Wang Yancheng Yuan Jiaming Ma T. Zeng Defeng Sun 32 3 0 29 Mar 2023
Exact Non-Oblivious Performance of Rademacher Random Embeddings Maciej Skorski Alessandro Temperoni 112 0 0 21 Mar 2023
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 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 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 Kuan Cheng S. Jiang Luojian Wei Zhide Wei 86 1 0 01 Oct 2022
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 Chris Schwiegelshohn Omar Ali Sheikh-Omar 39 11 0 03 Jul 2022
$k$ -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 Vincent Cohen-Addad Alessandro Epasto Silvio Lattanzi Vahab Mirrokni Andrés Muñoz David Saulpic Chris Schwiegelshohn Sergei Vassilvitskii FedML 54 16 0 17 Jun 2022
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 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 Vincent Cohen-Addad Kasper Green Larsen David Saulpic Chris Schwiegelshohn 56 51 0 25 Feb 2022
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! K. Makarychev Liren Shan 52 23 0 04 Nov 2021
Learning-Augmented $k$ -means Clustering Jon Ergun Zhili Feng Sandeep Silwal David P. Woodruff Samson Zhou 67 34 0 27 Oct 2021
Dimensionality Reduction for Wasserstein Barycenter Zachary Izzo Sandeep Silwal Samson Zhou 71 18 0 18 Oct 2021
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 Shyam Narayanan Sandeep Silwal Piotr Indyk Or Zamir 37 12 0 05 Jul 2021
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 Moses Charikar Lunjia Hu 57 18 0 29 Jun 2021
Locally Private $k$ -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 Alisa Chang Badih Ghazi Ravi Kumar Pasin Manurangsi 89 32 0 20 Apr 2021
Confidence-Optimal Random Embeddings Maciej Skorski 14 0 0 06 Apr 2021
Approximation Algorithms for Socially Fair Clustering Yury Makarychev A. Vakilian 78 50 0 03 Mar 2021
An Introduction to Johnson-Lindenstrauss Transforms Casper Benjamin Freksen 8 17 0 28 Feb 2021
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 40 0 0 08 Feb 2021
Fast and Accurate $k$ -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 Anup Bhattacharya Dishant Goyal Ragesh Jaiswal 34 9 0 09 Nov 2020
Improved Guarantees for k-means++ and k-means++ Parallel K. Makarychev Aravind Reddy Liren Shan DRL 80 24 0 27 Oct 2020