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dc.contributor.authorYom-Tov, Eladen_US
dc.contributor.editorBousquet, Olivieren_US
dc.contributor.editorLuxburg, Ulrike vonen_US
dc.contributor.editorRätsch, Gunnaren_US
dc.date.accessioned2019-04-09T03:08:45Z
dc.date.available2019-04-09T03:08:45Z
dc.date.issued2004en_US
dc.identifier.isbn9783540231226en_US
dc.identifier.isbn9783540286509en_US
dc.identifier.isbn3540231226en_US
dc.identifier.otherHPU1161270en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/32539
dc.description.abstractMachine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition, they provide in-depth overviews of exciting new developments and contain a large number of references. Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.en_US
dc.format.extent248 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.subjectAlgorithm Analysis and Problem Complexityen_US
dc.titleAdvanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2 - 14, 2003, Tübingen, Germany, August 4 - 16, 2003, Revised Lecturesen_US
dc.typeBooken_US
dc.size3,795 KBen_US
dc.departmentTechnologyen_US


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