Semi-supervised Learning in Network-Structured Data via Total Variation Minimization

28 January 2019

Papers citing "Semi-supervised Learning in Network-Structured Data via Total Variation Minimization"

12 / 12 papers shown

Title
Image Segmentation via Probabilistic Graph Matching Ayelet Heimowitz Y. Keller 40 20 0 13 May 2023
On The Complexity of Sparse Label Propagation A. Jung 71 10 0 25 Apr 2018
The Network Nullspace Property for Compressed Sensing of Big Data over Networks A. Jung Madelon Hulsebos 47 14 0 11 May 2017
When is Network Lasso Accurate? A. Jung Nguyen Tran Quang Alexandru Mara 108 40 0 07 Apr 2017
Community Detection and Stochastic Block Models Emmanuel Abbe 136 1,193 0 29 Mar 2017
Optimal rates for total variation denoising Jan-Christian Hütter Philippe Rigollet 42 33 0 30 Mar 2016
$Asymptotic behavior of $\ell_p$-based Laplacian regularization in semi-supervised learning$ Asymptotic behavior of $\ell_p$ -based Laplacian regularization in semi-supervised learning A. Alaoui Xiang Cheng Aaditya Ramdas Martin J. Wainwright Michael I. Jordan 39 54 0 02 Mar 2016
Algorithms for Lipschitz Learning on Graphs Rasmus Kyng Anup B. Rao Sushant Sachdeva D. Spielman 46 78 0 01 May 2015
Signal Recovery on Graphs: Variation Minimization Siheng Chen A. Sandryhaila José M. F. Moura J. Kovacevic 39 270 0 26 Nov 2014
Trend Filtering on Graphs Yu Wang James Sharpnack Alex Smola Robert Tibshirani 64 243 0 28 Oct 2014
Active Semi-Supervised Learning Using Sampling Theory for Graph Signals Akshay Gadde Aamir Anis Antonio Ortega 46 157 0 16 May 2014
A Tutorial on Spectral Clustering U. V. Luxburg 280 10,532 0 01 Nov 2007