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Ronitt Rubinfeld. Gouleakis, Themistoklis Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2019-02-14T15:51:15Z 2019-02-14T15:51:15Z 2018 2018 http://hdl.handle.net/1721.1/120434 1084486206 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 189-200). This thesis deals with sublinear algorithms for various types of problems in statistics, combinatorial optimization and graph algorithms. A first focus of this thesis is algorithms for testing whether a probability distribution, to which the algorithms have sample access, is equal to a given hypothesis distribution, using a number of samples that is sublinear in the domain size. A second focus is to consider various other models of computation defined by type of queries available to the user. This thesis shows how more powerful queries, such as the ability to get a sample according to the conditional distribution on a specified set, allows one to get faster algorithms for a number of problems. Thirdly, this thesis considers the problem of certifying and correcting the result of a crowdsourced computation with potentially erroneous worker reports, by using verification queries on a sublinear number of reports. Finally, we show improved methods to simulate graph algorithms for maximal independent set, minimum vertex cover and maximum matching by distributing the computation to multiple sublinear space computing machines and allowing only a sublinear number of rounds of communication between them. by Themistoklis Gouleakis. Ph.D. 200 pages eng Massachusetts Institute of Technology MIT 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. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. New directions in sublinear algorithms and testing properties of distributions Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="f3f0dbf3-ca5c-435c-8640-61375e85e78d"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>New directions in sublinear algorithms and testing properties of distributions</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <Authors> <Author> <DisplayName>Gouleakis, Themistoklis</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>This thesis deals with sublinear algorithms for various types of problems in statistics, combinatorial optimization and graph algorithms. A first focus of this thesis is algorithms for testing whether a probability distribution, to which the algorithms have sample access, is equal to a given hypothesis distribution, using a number of samples that is sublinear in the domain size. A second focus is to consider various other models of computation defined by type of queries available to the user. This thesis shows how more powerful queries, such as the ability to get a sample according to the conditional distribution on a specified set, allows one to get faster algorithms for a number of problems. Thirdly, this thesis considers the problem of certifying and correcting the result of a crowdsourced computation with potentially erroneous worker reports, by using verification queries on a sublinear number of reports. Finally, we show improved methods to simulate graph algorithms for maximal independent set, minimum vertex cover and maximum matching by distributing the computation to multiple sublinear space computing machines and allowing only a sublinear number of rounds of communication between them.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>