The Minimax Learning Rates of Normal and Ising Undirected Graphical Models

18 June 2018

Papers citing "The Minimax Learning Rates of Normal and Ising Undirected Graphical Models"

12 / 12 papers shown

Title
The total variation distance between high-dimensional Gaussians with the same mean Luc Devroye Abbas Mehrabian Tommy Reddad 45 225 0 19 Oct 2018
Near-optimal Sample Complexity Bounds for Robust Learning of Gaussians Mixtures via Compression Schemes H. Ashtiani Shai Ben-David Nicholas J. A. Harvey Christopher Liaw Abbas Mehrabian Y. Plan 25 5 0 14 Oct 2017
Learning Graphical Models Using Multiplicative Weights Adam R. Klivans Raghu Meka 37 112 0 20 Jun 2017
Sample-Efficient Learning of Mixtures H. Ashtiani Shai Ben-David Abbas Mehrabian 33 25 0 06 Jun 2017
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications Linus Hamilton Frederic Koehler Ankur Moitra 33 64 0 31 May 2017
Exact recovery in the Ising blockmodel Quentin Berthet Philippe Rigollet P. Srivastava TPM 52 45 0 12 Dec 2016
Testing Ising Models C. Daskalakis Nishanth Dikkala Gautam Kamath 47 101 0 09 Dec 2016
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models Marc Vuffray Sidhant Misra A. Lokhov Michael Chertkov 35 111 0 24 May 2016
Efficiently learning Ising models on arbitrary graphs Guy Bresler 60 202 0 22 Nov 2014
On the Information Theoretic Limits of Learning Ising Models Karthikeyan Shanmugam Rashish Tandon A. Dimakis Pradeep Ravikumar 42 36 0 05 Nov 2014
Near-optimal-sample estimators for spherical Gaussian mixtures A. Suresh Ashkan Jafarpour A. Orlitsky Jayadev Acharya 64 92 0 19 Feb 2014
Information-theoretic limits of selecting binary graphical models in high dimensions N. Santhanam Martin J. Wainwright 110 204 0 16 May 2009