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dc.contributor.advisorTomaso Poggio.en_US
dc.contributor.authorLiang, Robert Xinyu.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2019-12-05T18:06:51Z
dc.date.available2019-12-05T18:06:51Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/123163
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 47).en_US
dc.description.abstractIn the recent few years, deep learning has had great successes in many applications such as image recognition. However, theory seems to lag behind application in this field, and one goal has been to provide principles and solve puzzles. Some goals during this thesis work were to develop new software tools for deep learning researchers, run experiments related to the research of CBMM (Center for Brains, Minds, and Machines), and create graphs for papers published by CBMM.en_US
dc.description.statementofresponsibilityby Robert Xinyu Liang.en_US
dc.format.extent47 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleExperiments on the generalization and learning dynamics of deep neural networksen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.identifier.oclc1129252272en_US
dc.description.collectionM.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2019-12-05T18:06:50Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentEECSen_US


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