Sparse Graph Learning Under Laplacian-Related Constraints

16 November 2021

Papers citing "Sparse Graph Learning Under Laplacian-Related Constraints"

21 / 21 papers shown

Title
Learning Multi-Attribute Differential Graphs with Non-Convex Penalties Jitendra K Tugnait 747 0 0 14 May 2025
Graph Learning: A Survey Xiwei Xu Ke Sun Shuo Yu Abdul Aziz Liangtian Wan Shirui Pan Huan Liu GNN 87 353 0 03 May 2021
Learning Graph Laplacian with MCP Yangjing Zhang Kim-Chuan Toh Defeng Sun 67 7 0 22 Oct 2020
Structured Graph Learning for Clustering and Semi-supervised Classification Zhao Kang Chong Peng Q. Cheng Xinwang Liu Xi Peng Zenglin Xu Ling Tian 57 134 0 31 Aug 2020
Covariance estimation with nonnegative partial correlations Jake A. Soloff Adityanand Guntuboyina Michael I. Jordan 36 10 0 30 Jul 2020
A Unified Framework for Structured Graph Learning via Spectral Constraints Sandeep Kumar Jiaxi Ying José Vinícius de Miranda Cardoso Daniel P. Palomar 67 115 0 22 Apr 2019
Robust Graph Learning from Noisy Data Zhao Kang Haiqi Pan Guosheng Lin Zenglin Xu OOD NoLa 94 256 0 17 Dec 2018
Learning graphs from data: A signal representation perspective Xiaowen Dong D. Thanou Michael G. Rabbat P. Frossard 105 381 0 03 Jun 2018
Large Scale Graph Learning from Smooth Signals Vassilis Kalofolias Nathanael Perraudin 81 82 0 16 Oct 2017
Learning Graphs with Monotone Topology Properties and Multiple Connected Components Eduardo Pavez Hilmi E. Egilmez Antonio Ortega 65 55 0 31 May 2017
Maximum likelihood estimation in Gaussian models under total positivity Steffen Lauritzen Caroline Uhler Piotr Zwiernik 116 70 0 14 Feb 2017
How to learn a graph from smooth signals Vassilis Kalofolias 84 515 0 11 Jan 2016
Support recovery without incoherence: A case for nonconvex regularization Po-Ling Loh Martin J. Wainwright 172 169 0 17 Dec 2014
Estimation of positive definite M-matrices and structure learning for attractive Gaussian Markov Random fields M. Slawski Matthias Hein 123 104 0 26 Apr 2014
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima Po-Ling Loh Martin J. Wainwright 303 517 0 10 May 2013
Node-Based Learning of Multiple Gaussian Graphical Models Karthika Mohan Palma London Maryam Fazel Daniela Witten Su-In Lee 69 208 0 21 Mar 2013
$High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence$ High-dimensional covariance estimation by minimizing $\ell_1$ -penalized log-determinant divergence Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu 249 873 0 21 Nov 2008
Sparse permutation invariant covariance estimation Adam J. Rothman Peter J. Bickel Elizaveta Levina Ji Zhu 607 906 0 31 Jan 2008
Sparsistency and rates of convergence in large covariance matrix estimation Clifford Lam Jianqing Fan 233 610 0 26 Nov 2007
Enhancing Sparsity by Reweighted L1 Minimization Emmanuel J. Candes M. Wakin Stephen P. Boyd 217 5,045 0 10 Nov 2007
A Tutorial on Spectral Clustering U. V. Luxburg 290 10,543 0 01 Nov 2007