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Learning from imperfect data in theory and practice

dc.contributor.advisorRonald L. Rivest.en_US
dc.contributor.authorSlonim, Donna Ken_US
dc.date.accessioned2005-08-18T15:54:00Z
dc.date.available2005-08-18T15:54:00Z
dc.date.copyright1996en_US
dc.date.issued1996en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/11004
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.en_US
dc.descriptionIncludes bibliographical references (p. 167-176).en_US
dc.description.statementofresponsibilityby Donna Karen Slonim.en_US
dc.format.extent176 p.en_US
dc.format.extent15639925 bytes
dc.format.extent15639680 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Scienceen_US
dc.titleLearning from imperfect data in theory and practiceen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc35956924en_US


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