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Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity
Published on 2011-08-023757 Views
We extend Bayesian MAP and Minimum Description Length (MDL) learning by testing whether the data can be substantially more compressed by a mixture of the MDL/MAP distribution with another element of
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Presentation
Safe Learning00:00
Two Seemingly Different Problems - 100:09
Two Seemingly Different Problems - 203:06
Basic 2-part code MDL04:28
Convergence of 2-MDL - 106:14
Convergence of 2-MDL - 207:47
First Insight08:51
Bad and Good Misspecification - 109:16
Bad and Good Misspecification - 209:34
Bad and Good Misspecification - 309:39
Can we test (tell from the data) wether we are in the bad situation?10:38
YES: we can test wether it’s bad!11:27
Can we adjust model or priors to “repair” situation? - 112:34
Can we adjust model or priors to “repair” situation? - 214:12
YES: we can adjust models/priors to bad situation!14:58
Safe Estimation - 115:53
Safe Estimation - 216:24
Safe Estimation - 316:27
Safe Estimation - 417:08
Main Result - 117:39
Main Result - 218:19
Second Result: What Actually Happens19:04
Classification! - 119:44
Classification! - 220:19
Classification! - 320:53
Final Remarks22:07