Searching for "Erratum to "Asymptotics of Discrete MDL for Online Prediction"." – sorted by Relevance.
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Strong asymptotic assertions for discrete MDL in regression and classification
- that discrete MDL has good asymptotic predictive properties. On the other hand, the loss bounds for MDL
- Cited by 3 (2 self) – Add To MetaCart
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Strong Asymptotic Assertions for Discrete MDL in Regression and Classification
- show that discrete MDL has good asymptotic predictive properties. In particular, we have shown a finite
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MDL Tutorial
- several breakthroughs in the area of Minimum Description Length (MDL) modeling, learning and prediction
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Applying MDL to Learning Best Model Granularity
- methods, that is, of MDL and Bayesianism. 1.1 Introduction to Learning On-Line Handwritten Characters
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Suboptimal behavior of Bayes and MDL in classification under misspecification
- Bayes(P,S), the MAP classifier cmap(P,S), and the MDL classifier cmdl(P,S) are asymptotically suboptimal with respect
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On the Behavior of MDL Denoising
- On the Behavior of MDL Denoising Teemu Roos Petri Myllymäki Helsinki Institute for Information
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DCG Induction using MDL and Parsed Corpora
- DCG Induction using MDL and Parsed Corpora Miles Osborne Alfa Informatica, University
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Model selection using information theory and the mdl principle
- Model Selection using Information Theory and the MDL Principle ∗ Robert A. Stine Department
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PAC-MDL bounds
- on the future error rate of a resulting prediction procedure. In this section we show how the PAC-MDL bound can
- Cited by 10 (0 self) – Add To MetaCart
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PAC-MDL bounds
- on the future error rate of a resulting prediction procedure. In this section we show how the PAC-MDL bound can
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