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dc.contributor.author	Ferri Ramírez, César	es_ES
dc.contributor.author	Hernández Orallo, José	es_ES
dc.contributor.author	Telle, Jan Arne	es_ES
dc.date.accessioned	2022-05-03T05:59:23Z
dc.date.available	2022-05-03T05:59:23Z
dc.date.issued	2022-05-03T05:59:23Z
dc.identifier.uri	http://hdl.handle.net/10251/182361
dc.description.abstract	Over the past decades in the field of machine teaching, several restrictions have been introduced to avoid ‘cheating’, such as collusion-free or non-clashing teaching. However, these restrictions forbid several teaching situations that we intuitively consider natural and fair, especially those ‘changes of mind’ of the learner as more evidence is given, affecting the likelihood of concepts and ultimately their posteriors. Under a new generalised probabilistic teaching, not only do these non-cheating constraints look too narrow but we also show that the most relevant machine teaching models are particular cases of this framework: the consistency graph between concepts and elements simply becomes a joint probability distribution. We show a simple procedure that builds the witness joint distribution from the ground joint distribution. We prove a chain of relations, also with a theoretical lower bound, on the teaching dimension of the old and new models. Overall, this new setting is more general than the traditional machine teaching models, yet at the same time more intuitively capturing a less abrupt notion of non-cheating teaching.	es_ES
dc.language	Inglés	es_ES
dc.rights	Reserva de todos los derechos	es_ES
dc.subject	Machine teaching	es_ES
dc.subject.classification	LENGUAJES Y SISTEMAS INFORMATICOS	es_ES
dc.title	A Probabilistic Framework for Non-Cheating Machine Teaching	es_ES
dc.type	Artículo	es_ES
dc.type	Working Paper	es_ES
dc.rights.accessRights	Abierto	es_ES
dc.contributor.affiliation	Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació	es_ES
dc.contributor.affiliation	Universitat Politècnica de València. Grupo de Extensiones de la Programación Lógica (ELP)	es_ES
dc.description.bibliographicCitation	Ferri Ramírez, C.; Hernández Orallo, J.; Telle, JA. (2022). A Probabilistic Framework for Non-Cheating Machine Teaching. http://hdl.handle.net/10251/182361	es_ES
dc.type.version	info:eu-repo/semantics/draft	es_ES

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  ELP: Extensiones de la Programación Lógica (Extensions of Logic Programming)

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