Learning loopy graphical models with latent variables: Efficient methods and guarantees

17 March 2012

Papers citing "Learning loopy graphical models with latent variables: Efficient methods and guarantees"

27 / 27 papers shown

Title
Learning the Influence Graph of a High-Dimensional Markov Process with Memory Smita Bagewadi Avhishek Chatterjee CML 23 0 0 13 Jun 2024
Optimal estimation of Gaussian (poly)trees Yuhao Wang Ming Gao Wai Ming Tai Bryon Aragam Arnab Bhattacharyya TPM 32 1 0 09 Feb 2024
Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise Augusto Santos Diogo Rente Rui Seabra José M. F. Moura 19 4 0 10 Dec 2023
A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width Jason Gaitonde Elchanan Mossel 26 8 0 15 Nov 2023
Robust Model Selection of Gaussian Graphical Models Abrar Zahin Rajasekhar Anguluri Lalitha Sankar O. Kosut Gautam Dasarathy 11 0 0 10 Nov 2022
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach Sérgio Machado Anirudh Sridhar P. Gil J. Henriques J. M. F. Moura A. Santos CML 12 2 0 08 Aug 2022
Learning latent causal graphs via mixture oracles Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam CML 22 47 0 29 Jun 2021
Learning to Sample from Censored Markov Random Fields Ankur Moitra Elchanan Mossel Colin Sandon 16 7 0 15 Jan 2021
Learning Restricted Boltzmann Machines with Sparse Latent Variables Guy Bresler Rares-Darius Buhai 18 2 0 07 Jun 2020
Graph Learning Under Partial Observability Vincenzo Matta A. Santos Ali H. Sayed 19 0 0 18 Dec 2019
Topology Inference over Networks with Nonlinear Coupling A. Santos Vincenzo Matta Ali H. Sayed 29 0 0 21 Jun 2019
Learning Restricted Boltzmann Machines with Arbitrary External Fields Surbhi Goel 14 2 0 15 Jun 2019
Graph Learning over Partially Observed Diffusion Networks: Role of Degree Concentration Vincenzo Matta A. Santos Ali H. Sayed 14 2 0 05 Apr 2019
Predictive Learning on Hidden Tree-Structured Ising Models Konstantinos E. Nikolakakis Dionysios S. Kalogerias Anand D. Sarwate 23 12 0 11 Dec 2018
Learning Restricted Boltzmann Machines via Influence Maximization Guy Bresler Frederic Koehler Ankur Moitra Elchanan Mossel AI4CE 20 29 0 25 May 2018
Local Tomography of Large Networks under the Low-Observability Regime A. Santos Vincenzo Matta Ali H. Sayed 17 27 0 23 May 2018
Information Theoretic Structure Learning with Confidence Kevin R. Moon M. Noshad Salimeh Yasaei Sekeh Alfred Hero 11 18 0 13 Sep 2016
Discovery of Latent Factors in High-dimensional Data Using Tensor Methods Furong Huang 10 6 0 10 Jun 2016
Structure Learning in Graphical Modeling Mathias Drton Marloes H. Maathuis CML 39 246 0 07 Jun 2016
Learning a Tree-Structured Ising Model in Order to Make Predictions Guy Bresler Mina Karzand 55 46 0 22 Apr 2016
Graphical Fermat's Principle and Triangle-Free Graph Estimation Junwei Lu Han Liu 19 0 0 23 Apr 2015
A Hash-based Co-Clustering Algorithm for Categorical Data F. O. França 31 22 0 29 Jul 2014
Guaranteed Scalable Learning of Latent Tree Models Furong Huang U. Niranjan Ioakeim Perros Robert Chen Jimeng Sun Anima Anandkumar 26 7 0 18 Jun 2014
Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning Le Song Han Liu Ankur P. Parikh Eric P. Xing 68 9 0 16 Jan 2014
Learning Topic Models and Latent Bayesian Networks Under Expansion Constraints Anima Anandkumar Daniel J. Hsu Adel Javanmard Sham Kakade 35 8 0 24 Sep 2012
Learning High-Dimensional Mixtures of Graphical Models Anima Anandkumar Daniel J. Hsu F. Huang Sham Kakade 35 10 0 04 Mar 2012
Robust estimation of latent tree graphical models: Inferring hidden states with inexact parameters Elchanan Mossel S. Roch Allan Sly 26 19 0 21 Sep 2011