Bayes Risk
Bayes Risk is the expected value of the loss function under the joint distribution of the data and the true parameter, minimized over all possible decision rules, representing the lowest achievable expected loss in a Bayesian decision-theoretic framework.
428
Publications
22.2K
Citations
809
Authors
368
Institutions
Publications per year
2017–2026
71
Parents
428
Sequence-discriminative training of deep neural networks
Karel Veselý, Arnab Ghoshal, Lukáš Burget et al. · 2013 · 662 citations · Full text
Calibrating Probability with Undersampling for Unbalanced Classification
Andrea Dal Pozzolo, Olivier Caelen, R. A. Johnson et al. · 2015 · 606 citations
1–5 of 428
809
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IBM Research - Thomas J. Watson Research Center, United States
5 publications · 989 citations
5
h-index
1–5 of 809
368
Stanford University
Stanford, United States
13 h-index
33 publications
1.6K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
12 h-index
20 publications
2.2K citations
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
23 publications
1.2K citations

Johns Hopkins University
Baltimore, United States
10 h-index
17 publications
1.1K citations
Purdue University West Lafayette
West Lafayette, United States
7 h-index
10 publications
512 citations
Google (United States)
Mountain View, United States
6 h-index
21 publications
1K citations
University of Cambridge
Cambridge, United Kingdom
6 h-index
15 publications
789 citations
University of California San Diego
San Diego, United States
6 h-index
10 publications
695 citations
1–8 of 368
41 publications · 3.1K citations
24
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25 publications · 1.7K citations
18
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14 publications · 251 citations
12
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Repository · 15 publications · 366 citations
12
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11 publications · 1.8K citations
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