Bayesian Nonparametric Decision Making

Bayesian Nonparametric Decision Making is a decision-theoretic framework that extends Bayesian decision theory by employing nonparametric Bayesian models to flexibly adapt the complexity of the decision policy to the data, without assuming a fixed finite number of parameters.

5

Publications

121

Citations

11

Authors

11

Institutions

Publications per year

2017–2026

1

Authors

11

  1. SG
    Stephen G. Walker

    University of Kent, United Kingdom

    2 publications · 33 citations

    2

    h-index

  2. MK
    Miłosz Kadziński

    Poznań University of Technology, Poland

    1 publications · 30 citations

    1

    h-index

  3. XL
    Xiuwu Liao

    Xi'an Jiaotong University, China

    1 publications · 30 citations

    1

    h-index

  4. JL
    Jiapeng Liu

    Xi'an Jiaotong University, China

    1 publications · 30 citations

    1

    h-index

  5. JC
    Jae‐Won Choi

    University of Akron, United States

    1 publications · 11 citations

    1

    h-index

1–5 of 11

Venues

  1. INFORMS journal on computing

    1 publications · 30 citations

    1

    h-index

  2. 1

    h-index

  3. 1

    h-index

  4. Games and Economic Behavior

    1 publications · 11 citations

    1

    h-index

  5. International Statistical Review

    1 publications · 18 citations

    1

    h-index

1–5