List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians

20 November 2017

Papers citing "List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians"

43 / 43 papers shown

Title
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination Ilias Diakonikolas Giannis Iakovidis D. Kane Thanasis Pittas 87 0 0 20 Feb 2025
Entangled Mean Estimation in High-Dimensions Ilias Diakonikolas D. Kane Sihan Liu Thanasis Pittas 45 1 0 10 Jan 2025
LiD-FL: Towards List-Decodable Federated Learning Hong Liu Liren Shan Han Bao Ronghui You Yuhao Yi Jiancheng Lv FedML 49 0 0 09 Aug 2024
SQ Lower Bounds for Learning Mixtures of Linear Classifiers Ilias Diakonikolas D. Kane Yuxin Sun 30 3 0 18 Oct 2023
Private Distribution Learning with Public Data: The View from Sample Compression Shai Ben-David Alex Bie C. Canonne Gautam Kamath Vikrant Singhal 49 11 0 11 Aug 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers Puning Zhao Zhiguo Wan OOD FedML 50 4 0 25 Jul 2023
SQ Lower Bounds for Learning Bounded Covariance GMMs Ilias Diakonikolas D. Kane Thanasis Pittas Nikos Zarifis 40 0 0 22 Jun 2023
On the robust learning mixtures of linear regressions Ying-Min Huang Liang Chen OOD 21 0 0 23 May 2023
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas OOD 36 10 0 04 May 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 41 9 0 30 Jan 2023
Efficient List-Decodable Regression using Batches Abhimanyu Das Ayush Jain Weihao Kong Rajat Sen 28 4 0 23 Nov 2022
A Characterization of List Learnability Moses Charikar Chirag Pabbaraju 37 13 0 07 Nov 2022
A Fourier Approach to Mixture Learning Mingda Qiao Guru Guruganesh A. S. Rawat Kumar Avinava Dubey Manzil Zaheer 22 3 0 05 Oct 2022
List-Decodable Covariance Estimation Misha Ivkov Pravesh Kothari 24 7 0 22 Jun 2022
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models Ilias Diakonikolas D. Kane Yuxin Sun 33 1 0 09 Jun 2022
Robust Sparse Mean Estimation via Sum of Squares Ilias Diakonikolas D. Kane Sushrut Karmalkar Ankit Pensia Thanasis Pittas 28 21 0 07 Jun 2022
List-Decodable Sparse Mean Estimation Shiwei Zeng Jie Shen 29 9 0 28 May 2022
Streaming Algorithms for High-Dimensional Robust Statistics Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas 24 21 0 26 Apr 2022
Continuous LWE is as Hard as LWE & Applications to Learning Gaussian Mixtures A. Gupte Neekon Vafa Vinod Vaikuntanathan 25 39 0 06 Apr 2022
Differentially-Private Clustering of Easy Instances E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer Eliad Tsfadia 27 22 0 29 Dec 2021
Non-Gaussian Component Analysis via Lattice Basis Reduction Ilias Diakonikolas D. Kane 41 18 0 16 Dec 2021
Lattice-Based Methods Surpass Sum-of-Squares in Clustering Ilias Zadik M. Song Alexander S. Wein Joan Bruna 22 35 0 07 Dec 2021
Clustering Mixtures with Almost Optimal Separation in Polynomial Time Jingkai Li Allen Liu 30 23 0 01 Dec 2021
Kalman Filtering with Adversarial Corruptions Sitan Chen Frederic Koehler Ankur Moitra Morris Yau AAML 27 10 0 11 Nov 2021
Robust Estimation for Random Graphs Jayadev Acharya Ayush Jain Gautam Kamath A. Suresh Huanyu Zhang 32 8 0 09 Nov 2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition Ilias Diakonikolas D. Kane Alistair Stewart Yuxin Sun 24 15 0 03 Feb 2021
SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation David Steurer Stefan Tiegel 29 10 0 05 Jan 2021
Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models Ilias Diakonikolas D. Kane 21 32 0 14 Dec 2020
Optimal Mean Estimation without a Variance Yeshwanth Cherapanamjeri Nilesh Tripuraneni Peter L. Bartlett Michael I. Jordan 26 21 0 24 Nov 2020
Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding Di Wang Xiangyu Guo Shi Li Jinhui Xu 23 3 0 19 Oct 2020
Optimal Robust Linear Regression in Nearly Linear Time Yeshwanth Cherapanamjeri Efe Aras Nilesh Tripuraneni Michael I. Jordan Nicolas Flammarion Peter L. Bartlett 35 35 0 16 Jul 2020
Robustly Learning any Clusterable Mixture of Gaussians Ilias Diakonikolas Samuel B. Hopkins D. Kane Sushrut Karmalkar 38 45 0 13 May 2020
Outlier-Robust Clustering of Non-Spherical Mixtures Ainesh Bakshi Pravesh Kothari 27 31 0 06 May 2020
List Decodable Subspace Recovery P. Raghavendra Morris Yau 38 25 0 07 Feb 2020
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering Ilias Diakonikolas Sushrut Karmalkar D. Kane Eric Price Alistair Stewart 23 41 0 19 Nov 2019
Robust subgaussian estimation of a mean vector in nearly linear time Jules Depersin Guillaume Lecué 21 92 0 07 Jun 2019
List-Decodable Linear Regression Sushrut Karmalkar Adam R. Klivans Pravesh Kothari 34 74 0 14 May 2019
The Optimal Approximation Factor in Density Estimation Olivier Bousquet D. Kane Shay Moran 19 18 0 10 Feb 2019
Iterative Least Trimmed Squares for Mixed Linear Regression Yanyao Shen Sujay Sanghavi 27 25 0 10 Feb 2019
Conditional Linear Regression Diego Calderon Brendan Juba Sirui Li Zong-Yi Li Lisa Ruan 20 4 0 06 Jun 2018
Efficient Algorithms and Lower Bounds for Robust Linear Regression Ilias Diakonikolas Weihao Kong Alistair Stewart 27 161 0 31 May 2018
Robust Learning of Fixed-Structure Bayesian Networks Yu Cheng Ilias Diakonikolas D. Kane Alistair Stewart OOD 46 46 0 23 Jun 2016
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane Jingkai Li Ankur Moitra Alistair Stewart 21 505 0 21 Apr 2016