Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications

31 May 2017

Papers citing "Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications"

26 / 26 papers shown

Title
Learning Juntas under Markov Random Fields Gautam Chandrasekaran Adam R. Klivans 33 0 0 01 Jun 2025
One-Shot Learning for k-SAT Andreas Galanis Leslie Ann Goldberg Xusheng Zhang 65 0 0 10 Feb 2025
Efficient Hamiltonian, structure and trace distance learning of Gaussian states Marco Fanizza Cambyse Rouzé Daniel Stilck França 85 6 0 05 Nov 2024
Discrete distributions are learnable from metastable samples Abhijith Jayakumar A. Lokhov Sidhant Misra Marc Vuffray 222 1 0 17 Oct 2024
Structure learning of Hamiltonians from real-time evolution Ainesh Bakshi Allen Liu Ankur Moitra Ewin Tang 102 14 0 30 Apr 2024
Estimating the interaction graph of stochastic neuronal dynamics by observing only pairs of neurons E. Santis A. Galves G. Nappo M. Piccioni 32 5 0 14 Jun 2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition Ilias Diakonikolas D. Kane Alistair Stewart Yuxin Sun 77 16 0 03 Feb 2021
Sample-Optimal and Efficient Learning of Tree Ising models C. Daskalakis Qinxuan Pan 64 8 0 28 Oct 2020
Estimation in Tensor Ising Models Somabha Mukherjee Jaesung Son B. Bhattacharya 77 12 0 29 Aug 2020
Parameter Estimation for Undirected Graphical Models with Hard Constraints B. Bhattacharya K. Ramanan 78 2 0 22 Aug 2020
Learning of Discrete Graphical Models with Neural Networks Abhijith Jayakumar A. Lokhov Sidhant Misra Marc Vuffray CML 60 8 0 21 Jun 2020
Robust Estimation of Tree Structured Ising Models A. Katiyar Vatsal Shah Constantine Caramanis TPM 64 10 0 10 Jun 2020
Learning Restricted Boltzmann Machines with Sparse Latent Variables Guy Bresler Rares-Darius Buhai 42 2 0 07 Jun 2020
Hardness of Identity Testing for Restricted Boltzmann Machines and Potts models Antonio Blanca Zongchen Chen Daniel Stefankovic Eric Vigoda 55 4 0 22 Apr 2020
Learning Ising models from one or multiple samples Y. Dagan C. Daskalakis Nishanth Dikkala Anthimos Vardis Kandiros 66 10 0 20 Apr 2020
Logistic-Regression with peer-group effects via inference in higher order Ising models C. Daskalakis Nishanth Dikkala Ioannis Panageas 57 11 0 18 Mar 2020
Privately Learning Markov Random Fields Huanyu Zhang Gautam Kamath Janardhan Kulkarni Zhiwei Steven Wu 88 25 0 21 Feb 2020
Regression from Dependent Observations C. Daskalakis Nishanth Dikkala Ioannis Panageas 89 30 0 08 May 2019
Learning Ising Models with Independent Failures Surbhi Goel D. Kane Adam R. Klivans 55 16 0 13 Feb 2019
Efficient Learning of Discrete Graphical Models Marc Vuffray Sidhant Misra A. Lokhov 61 35 0 02 Feb 2019
Lower bounds for testing graphical models: colorings and antiferromagnetic Ising models Ivona Bezáková Antonio Blanca Zongchen Chen Daniel Stefankovic Eric Vigoda 88 20 0 22 Jan 2019
Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models Shanshan Wu Sujay Sanghavi A. Dimakis 82 51 0 28 Oct 2018
The Minimax Learning Rates of Normal and Ising Undirected Graphical Models Luc Devroye Abbas Mehrabian Tommy Reddad 63 30 0 18 Jun 2018
Learning Restricted Boltzmann Machines via Influence Maximization Guy Bresler Frederic Koehler Ankur Moitra Elchanan Mossel AI4CE 70 29 0 25 May 2018
Learning Graphical Models Using Multiplicative Weights Adam R. Klivans Raghu Meka 90 113 0 20 Jun 2017
Testing Ising Models C. Daskalakis Nishanth Dikkala Gautam Kamath 129 101 0 09 Dec 2016