The Consistency dimension and distribution-dependent learning from queries
We prove a new combinatorial characterization of polynomial learnability from equivalence queries, and state some of its consequences relating the learnability of a class with the learnability via equivalence and membership queries of its subclasses obtained by restricting the instance space. Then w...
| Autores: | , , |
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| Tipo de documento: | relatório científico |
| Data de publicação: | 2000 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/95948 |
| Acesso em linha: | https://hdl.handle.net/2117/95948 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Combinatorial characterization Polynomial learnability Query learning Àrees temàtiques de la UPC::Informàtica |
| Resumo: | We prove a new combinatorial characterization of polynomial learnability from equivalence queries, and state some of its consequences relating the learnability of a class with the learnability via equivalence and membership queries of its subclasses obtained by restricting the instance space. Then we propose and study two models of query learning in which there is a probability distribution on the instance space, both as an application of the tools developed from the combinatorial characterization and as models of independent interest. |
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