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Asymptotic Bayesian generalization error when training and test distributions are different
Keisuke Yamazaki
*
, Motoaki Kawanabe
, Sumio Watanabe
, Masashi Sugiyama
,
Klaus Robert Müller
*
Corresponding author for this work
Research output
:
Contribution to conference
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Paper
›
peer-review
30
Citations (Scopus)
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Keyphrases
Distribution Change
100%
Generalization Error
100%
Training Distribution
100%
Test Distribution
100%
Supervised Learning
33%
Machine Learning Techniques
33%
Appropriate Model
33%
Hyperparameters
33%
Bayesian Estimation
33%
Lower Order Terms
33%
Novel Variants
33%
Stochastic Complexity
33%
Mathematics
Asymptotics
100%
Bayesian
100%
Upper Bound
50%
Test Data
50%
Training Data
50%
Bayesian Estimation
50%
Lower Order Term
50%
Stochastic Complexity
50%
Computer Science
Generalization Error
100%
Supervised Learning
50%
Machine Learning Technique
50%
Bayes Estimator
50%
Economics, Econometrics and Finance
Bayesian
100%
Machine Learning
33%