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Predictive PAC Learning and Process Decompositions

We informally call a stochastic process learnable if it admits a generalization error approaching zero in probability for any concept class with finite VC-dimension (IID processes are the simplest example). A mixture of learnable processes need not be learnable itself, and certainly its generalizati...

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Bibliografiske detaljer
Udgivet i:Adv Neural Inf Process Syst
Main Authors: Shalizi, Cosma Rohilla, Kontorovich, Aryeh
Format: Artigo
Sprog:Inglês
Udgivet: 2013
Fag:
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4551412/
https://ncbi.nlm.nih.gov/pubmed/26321855
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