Robust Risk Estimation

Robust Risk Estimation is a formal methodology in statistical and machine learning contexts that characterizes uncertainty in risk assessment by ensuring stability and reliability of risk predictions under distributional perturbations or data outliers.

104

Publications

4.7K

Citations

217

Authors

142

Institutions

Publications per year

2017–2026

30

Authors

217

  1. SK
    Steven Kou

    Columbia University, United States

    3 publications · 247 citations

    3

    h-index

  2. CC
    C. C. Heyde

    Australian National University, Australia

    3 publications · 247 citations

    3

    h-index

  3. XP
    Xianhua Peng

    Columbia University, United States

    3 publications · 247 citations

    3

    h-index

  4. GS
    Gerhard Stahl

    University of Duisburg-Essen, Germany

    2 publications · 46 citations

    2

    h-index

  5. KN
    Karthik Natarajan

    National University of Singapore, Singapore

    2 publications · 318 citations

    2

    h-index

1–5 of 217

Venues

  1. SSRN Electronic Journal

    Repository · 9 publications · 188 citations

    9

    h-index

  2. Insurance Mathematics and Economics

    4 publications · 97 citations

    4

    h-index

  3. Operations Research

    4 publications · 361 citations

    4

    h-index

  4. Quantitative Finance

    3 publications · 279 citations

    3

    h-index

  5. European Journal of Operational Research

    3 publications · 178 citations

    3

    h-index

1–5