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Suboptimality of MDL and Bayes in Classification under Misspecification
Published on Feb 4, 20253216 Views
We show that forms of Bayesian and MDL learning that are often applied to classification problems can be *statistically inconsistent*. We present a large family of classifiers and a distribution such
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Presentation
Suboptimality of Bayes and MDL in Classification00:02
Our Result00:29
Why is this interesting?01:17
Menu02:39
Classification03:22
Classification Models04:26
Generalization Error05:05
Learning Algorithms06:02
Consistent Learning Algorithms06:38
Main Result08:09
Remainder of Talk13:07
Bayesian Learning of Classifiers13:40
classifiers probability distrs.14:53
Logistic transformation - intuition16:25
Definition of . 24:55
Issues/Remainder of Talk27:21
Scenario27:36
Scenario – II: Definition of true D29:35
Result: 31:16
Theorem 137:20
Theorem 1, extended 39:33
How ‘natural’ is scenario?42:46
Thm 2: full Bayes result is ‘tight’ 45:46
Theorem 247:38
Proof Sketch49:46
Wait a minute…55:35
Bayes predicts too well58:52
Bayesian Consistency Results01:00:11
Bayesian consistency under misspecification01:02:58
Conclusion01:05:21