Probabilistic inductive inference: A survey

Andris Ambainis

doi:10.1016/S0304-3975(00)00218-8

Probabilistic inductive inference: A survey

Andris Ambainis^*

^*Šī darba korespondējošais autors

University of California at Berkeley

Zinātniskās darbības rezultāts: Devums žurnālam › Zinātniskais raksts (žurnālā) › koleģiāli recenzēts

7 Atsauces (Scopus)

Kopsavilkums

The developments in probabilistic inductive inference, learning, of recursive functions are presented. The paradigm of finite learning is analyzed. Classes of functions identifiable by probabilistic algorithms with different probabilities of correct answer are investigated.

Oriģinālvaloda	Angļu
Lapas (no-līdz)	155-167
Lapu skaits	13
Žurnāls	Theoretical Computer Science
Sējums	264
Izdevuma numurs	1
DOIs	https://doi.org/10.1016/S0304-3975(00)00218-8
Publikācijas statuss	Publicēts - 2001
Ārēji publicēts	Jā

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KW - Randomized computation

UR - https://www.scopus.com/pages/publications/0034894469

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DO - 10.1016/S0304-3975(00)00218-8

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JO - Theoretical Computer Science

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Probabilistic inductive inference: A survey

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