Safe Transfer Learning

Safe Transfer Learning is a transfer learning methodology that ensures the reliable and risk-minimized adaptation of knowledge from a source domain to a target domain while preserving safety constraints throughout the learning and deployment process.

4

Publications

278

Citations

18

Authors

9

Institutions

Publications per year

2017–2026

2

Authors

18

  1. JW
    Jianmin Wang

    Tsinghua University, China

    1 publications · 103 citations

    1

    h-index

  2. KA
    Kristen A. Rost

    Queens College, CUNY, United States

    1 publications · 10 citations

    1

    h-index

  3. SW
    Sinan Wang

    Tsinghua University, China

    1 publications · 103 citations

    1

    h-index

  4. DY
    Dit‐Yan Yeung

    Hong Kong University of Science and Technology, Hong Kong SAR China

    1 publications · 141 citations

    1

    h-index

  5. HF
    Hazem Fahmy

    University of Ottawa, Canada

    1 publications · 24 citations

    1

    h-index

1–5 of 18

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 141 citations

    1

    h-index

  2. Neural Information Processing Systems

    Conference · 1 publications · 103 citations

    1

    h-index

  3. Behavior Analysis in Practice

    1 publications · 10 citations

    1

    h-index

  4. ACM Transactions on Software Engineering and Methodology

    TOSEM · 1 publications · 24 citations

    1

    h-index

  5. IEEE Transactions on Cybernetics

    1 publications · 11 citations

1–5