Active Semi-Supervised Learning Using Sampling Theory for Graph Signals

16 May 2014

Papers citing "Active Semi-Supervised Learning Using Sampling Theory for Graph Signals"

26 / 26 papers shown

Title
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning Romain Cosentino Sarath Shekkizhar Mahdi Soltanolkotabi A. Avestimehr Antonio Ortega SSL 96 7 0 18 Sep 2022
Abstract message passing and distributed graph signal processing Feng Ji Y. Lu Wee Peng Tay Edwin K. P. Chong 120 0 0 09 Jun 2022
Multiscale Laplacian Learning Ekaterina Merkurjev D. Nguyen Guo-Wei Wei 77 4 0 08 Sep 2021
Sampling and Recovery of Graph Signals based on Graph Neural Networks Siheng Chen Maosen Li Ya Zhang 144 4 0 03 Nov 2020
When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision Yanqiao Zhu Weizhi Xu Qiang Liu Shu Wu 116 0 0 30 Oct 2020
Graph Policy Network for Transferable Active Learning on Graphs Shengding Hu Zheng Xiong Meng Qu Xingdi Yuan Marc-Alexandre Côté Zhiyuan Liu Jian Tang GNN 214 67 0 24 Jun 2020
Sampling Signals on Graphs: From Theory to Applications Yuichi Tanaka Yonina C. Eldar Antonio Ortega Gene Cheung 58 10 0 09 Mar 2020
GraphBGS: Background Subtraction via Recovery of Graph Signals Jhony H. Giraldo T. Bouwmans 112 25 0 17 Jan 2020
Robust Deep Graph Based Learning for Binary Classification Minxiang Ye V. Stanković L. Stanković Gene Cheung OOD 71 12 0 06 Dec 2019
Graph-based Semi-Supervised & Active Learning for Edge Flows Junteng Jia Michael T. Schaub Santiago Segarra Austin R. Benson 114 77 0 17 May 2019
GFCN: A New Graph Convolutional Network Based on Parallel Flows Feng Ji Jielong Yang Qiang Zhang Wee Peng Tay GNN 26 6 0 25 Feb 2019
Approximating Spectral Clustering via Sampling: a Review Nicolas M Tremblay Andreas Loukas 70 46 0 29 Jan 2019
Semi-supervised Learning in Network-Structured Data via Total Variation Minimization A. Jung A. Hero III Alexandru Mara Saeed Jahromi Ayelet Heimowitz Yonina C. Eldar 72 31 0 28 Jan 2019
Learning graphs from data: A signal representation perspective Xiaowen Dong D. Thanou Michael G. Rabbat P. Frossard 134 381 0 03 Jun 2018
On The Complexity of Sparse Label Propagation A. Jung 89 10 0 25 Apr 2018
MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis Rushil Anirudh Jayaraman J. Thiagarajan R. Sridhar T. Bremer FAtt AAML 72 12 0 15 Nov 2017
A random matrix analysis and improvement of semi-supervised learning for large dimensional data Xiaoyi Mai Romain Couillet 144 42 0 09 Nov 2017
A Sampling Theory Perspective of Graph-based Semi-supervised Learning Aamir Anis Aly El Gamal A. Avestimehr Antonio Ortega 145 44 0 26 May 2017
When is Network Lasso Accurate? A. Jung Nguyen Tran Quang Alexandru Mara 144 40 0 07 Apr 2017
Semi-Supervised Learning with Competitive Infection Models Nir Rosenfeld Amir Globerson SSL 169 6 0 19 Mar 2017
Guided Signal Reconstruction Theory A. Knyazev Akshay Gadde Hassan Mansour Dong Tian 135 3 0 02 Feb 2017
Robust Semi-Supervised Graph Classifier Learning with Negative Edge Weights Gene Cheung Weng-Tai Su Yu Mao Chia-Wen Lin 81 31 0 15 Nov 2016
Distributed Adaptive Learning of Graph Signals P. Lorenzo P. Banelli Sergio Barbarossa S. Sardellitti 104 63 0 20 Sep 2016
Active Learning for Community Detection in Stochastic Block Models Akshay Gadde Eyal En Gad A. Avestimehr Antonio Ortega 60 15 0 08 May 2016
A Probabilistic Interpretation of Sampling Theory of Graph Signals Akshay Gadde Antonio Ortega 119 73 0 23 Mar 2015
Asymptotic Justification of Bandlimited Interpolation of Graph signals for Semi-Supervised Learning Aamir Anis Aly El Gamal A. Avestimehr Antonio Ortega 125 19 0 14 Feb 2015