Outlier-Robust Learning of Ising Models Under Dobrushin's Condition

3 February 2021

Papers citing "Outlier-Robust Learning of Ising Models Under Dobrushin's Condition"

31 / 31 papers shown

Title
Robustly Learning Mixtures of $k$ Arbitrary Gaussians Ainesh Bakshi Ilias Diakonikolas Hengrui Jia D. Kane Pravesh Kothari Santosh Vempala 49 64 0 03 Dec 2020
Near-Optimal Learning of Tree-Structured Distributions by Chow-Liu Arnab Bhattacharyya Sutanu Gayen Eric Price N. V. Vinodchandran 40 23 0 09 Nov 2020
Settling the Robust Learnability of Mixtures of Gaussians Allen Liu Ankur Moitra 57 41 0 06 Nov 2020
Sample-Optimal and Efficient Learning of Tree Ising models C. Daskalakis Qinxuan Pan 40 7 0 28 Oct 2020
Robust Estimation of Tree Structured Ising Models A. Katiyar Vatsal Shah Constantine Caramanis TPM 40 10 0 10 Jun 2020
Robustly Learning any Clusterable Mixture of Gaussians Ilias Diakonikolas Samuel B. Hopkins D. Kane Sushrut Karmalkar 55 45 0 13 May 2020
Outlier-Robust Clustering of Non-Spherical Mixtures Ainesh Bakshi Pravesh Kothari 60 31 0 06 May 2020
Learning Ising models from one or multiple samples Y. Dagan C. Daskalakis Nishanth Dikkala Anthimos Vardis Kandiros 33 10 0 20 Apr 2020
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering Ilias Diakonikolas Sushrut Karmalkar D. Kane Eric Price Alistair Stewart 39 41 0 19 Nov 2019
Recent Advances in Algorithmic High-Dimensional Robust Statistics Ilias Diakonikolas D. Kane OOD 53 182 0 14 Nov 2019
Faster Algorithms for High-Dimensional Robust Covariance Estimation Yu Cheng Ilias Diakonikolas Rong Ge David P. Woodruff 47 66 0 11 Jun 2019
Learning Ising Models with Independent Failures Surbhi Goel D. Kane Adam R. Klivans 37 16 0 13 Feb 2019
Spectral Signatures in Backdoor Attacks Brandon Tran Jerry Li Aleksander Madry AAML 85 784 0 01 Nov 2018
Moving Beyond Sub-Gaussianity in High-Dimensional Statistics: Applications in Covariance Estimation and Linear Regression Arun K. Kuchibhotla Abhishek Chakrabortty 56 108 0 08 Apr 2018
Sever: A Robust Meta-Algorithm for Stochastic Optimization Ilias Diakonikolas Gautam Kamath D. Kane Jerry Li Jacob Steinhardt Alistair Stewart 57 289 0 07 Mar 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 57 221 0 19 Feb 2018
List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians Ilias Diakonikolas D. Kane Alistair Stewart 77 147 0 20 Nov 2017
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data C. Daskalakis Nishanth Dikkala Gautam Kamath 43 23 0 11 Oct 2017
Learning Graphical Models Using Multiplicative Weights Adam R. Klivans Raghu Meka 53 113 0 20 Jun 2017
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications Linus Hamilton Frederic Koehler Ankur Moitra 47 64 0 31 May 2017
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers Jacob Steinhardt Moses Charikar Gregory Valiant 61 138 0 15 Mar 2017
Being Robust (in High Dimensions) Can Be Practical Ilias Diakonikolas Gautam Kamath D. Kane Jerry Li Ankur Moitra Alistair Stewart 69 254 0 02 Mar 2017
Robust Learning of Fixed-Structure Bayesian Networks Yu Cheng Ilias Diakonikolas D. Kane Alistair Stewart OOD 57 46 0 23 Jun 2016
Agnostic Estimation of Mean and Covariance Kevin A. Lai Anup B. Rao Santosh Vempala 79 344 0 24 Apr 2016
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane Jingkai Li Ankur Moitra Alistair Stewart 66 510 0 21 Apr 2016
Structure learning of antiferromagnetic Ising models Guy Bresler D. Gamarnik Devavrat Shah 80 43 0 03 Dec 2014
Efficiently learning Ising models on arbitrary graphs Guy Bresler 65 203 0 22 Nov 2014
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses Po-Ling Loh Martin J. Wainwright 74 180 0 03 Dec 2012
Information-theoretic limits of selecting binary graphical models in high dimensions N. Santhanam Martin J. Wainwright 130 204 0 16 May 2009
$High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression$ High-Dimensional Graphical Model Selection Using $\ell_1$ -Regularized Logistic Regression Pradeep Ravikumar Martin J. Wainwright John D. Lafferty 270 177 0 26 Apr 2008
Reconstruction of Markov Random Fields from Samples: Some Easy Observations and Algorithms Guy Bresler Elchanan Mossel Allan Sly 93 159 0 10 Dec 2007