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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...
Uloženo v:
| Vydáno v: | Adv Neural Inf Process Syst |
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| Hlavní autoři: | , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2013
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4551412/ https://ncbi.nlm.nih.gov/pubmed/26321855 |
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