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dc.contributor.authorBalcázar, Jose L.en_US
dc.contributor.authorLong, Philip M.en_US
dc.contributor.authorStephan, Franken_US
dc.date.accessioned2019-03-26T08:29:24Z
dc.date.available2019-03-26T08:29:24Z
dc.date.issued2006en_US
dc.identifier.isbn9783540466499en_US
dc.identifier.isbn3540466495en_US
dc.identifier.otherHPU1161228en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/32301
dc.description.abstractThis book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006. The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning. They address topics such as query models, on-line learning, inductive inference, algorithmic forecasting, boosting, support vector machines, kernel methods, reinforcement learning, and statistical learning models.en_US
dc.format.extent404 p.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoenen_US
dc.publisherSpringer-Verlag Berlin Heidelbergen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectTechnologyen_US
dc.subjectComputationen_US
dc.titleAlgorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006. Proceedingsen_US
dc.typeBooken_US
dc.size4,003 KBen_US
dc.departmentTechnologyen_US


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