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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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書目詳細資料
發表在:Adv Neural Inf Process Syst
Main Authors: Shalizi, Cosma Rohilla, Kontorovich, Aryeh
格式: Artigo
語言:Inglês
出版: 2013
主題:
在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC4551412/
https://ncbi.nlm.nih.gov/pubmed/26321855
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