Structured Prediction

Structured Prediction is a supervised learning framework that generalizes standard classification and regression by predicting structured outputs—such as sequences, trees, or graphs—rather than scalar labels, leveraging dependencies among output variables to achieve coherent joint predictions.

384

Publications

39.6K

Citations

848

Authors

295

Institutions

Publications per year

2017–2026

143

Authors

848

  1. AG
    Amir Globerson

    Hebrew University of Jerusalem, Israel

    11 publications · 626 citations

    10

    h-index

  2. BT
    Ben Taskar

    University of Pennsylvania, United States

    10 publications · 853 citations

    10

    h-index

  3. JA
    J. Andrew Bagnell

    Carnegie Mellon University, United States

    9 publications · 2.8K citations

    9

    h-index

  4. EP
    Eric P. Xing

    Carnegie Mellon University, United States

    7 publications · 188 citations

    7

    h-index

  5. TH
    Tamir Hazan

    Technion – Israel Institute of Technology, Israel

    7 publications · 446 citations

    7

    h-index

1–5 of 848

Venues

  1. arXiv (Cornell University)

    Repository · 94 publications · 10.4K citations

    37

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 645 citations

    11

    h-index

  3. Neural Information Processing Systems

    Conference · 11 publications · 507 citations

    11

    h-index

  4. 9

    h-index

  5. Machine Learning

    6 publications · 168 citations

    6

    h-index

1–5