Concepedia

Graph Active Learning

Graph Active Learning is a machine learning paradigm within graph-based learning where the model iteratively selects the most informative nodes or edges to label, thereby optimizing the knowledge gain per annotation while leveraging the graph's structural relationships to improve learning efficiency and performance.

52

Publications

1.8K

Citations

170

Authors

85

Institutions

Publications per year

2017–2026

27

Parents

Publications

52

Active Learning for Networked Data

Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor · 2010 · 149 citations

, , +12

Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval

Xiaofei He · IEEE Transactions on Image Processing · 2009 · 108 citations

, , +16

A Variance Minimization Criterion to Active Learning on Graphs

Ji Ming, Jiawei Han · 2012 · 70 citations

, , +14

Adversarial Active Learning Based Heterogeneous Graph Neural Network for Fake News Detection

Yuxiang Ren, Bo Wang, Jiawei Zhang et al. · 2020 · 69 citations

, , +16

Graph-based Semi-Supervised & Active Learning for Edge Flows

2019 · 60 citations · Full text

, , +15

1–5 of 52

Authors

170

  1. RD
    Robert D. Nowak

    University of Wisconsin–Madison, United States

    3 publications · 37 citations

    3

    h-index

  2. HX
    Huan Xu

    Sichuan University, China

    2 publications · 36 citations

    2

    h-index

  3. BC
    Bin Cui

    Peking University, China

    2 publications · 46 citations

    2

    h-index

  4. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    2 publications · 115 citations

    2

    h-index

  5. ZY
    Zhi Yang

    Peking University, China

    2 publications · 46 citations

    2

    h-index

1–5 of 170

Institutions

85

  1. University of Illinois Urbana-Champaign

    Urbana, United States

    3 h-index

    7 publications

    263 citations

  2. Zhejiang University

    Hangzhou, China

    3 h-index

    9 publications

    425 citations

  3. Carnegie Mellon University

    Pittsburgh, United States

    3 h-index

    8 publications

    248 citations

  4. Peking University

    Beijing, China

    2 h-index

    9 publications

    220 citations

  5. University of Bern

    Bern, Switzerland

    2 h-index

    6 publications

    84 citations

  6. Microsoft Research (United Kingdom)

    Cambridge, United Kingdom

    2 h-index

    5 publications

    195 citations

  7. Science and Technology Facilities Council

    Swindon, United Kingdom

    1 h-index

    2 publications

    66 citations

  8. Jilin University

    Changchun, China

    1 h-index

    2 publications

    138 citations

1–8 of 85

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 211 citations

    9

    h-index

  2. Neurocomputing

    3 publications · 83 citations

    3

    h-index

  3. Applied Physics Reviews

    1 publications · 30 citations

    1

    h-index

  4. Machine Learning Science and Technology

    1 publications · 44 citations

    1

    h-index

  5. Frontiers in Neuroinformatics

    1 publications · 55 citations

    1

    h-index

1–5