{"id":37827,"date":"2014-09-01T22:07:52","date_gmt":"2014-09-02T03:07:52","guid":{"rendered":"https:\/\/www.bu.edu\/cise\/?post_type=research&#038;p=37827"},"modified":"2022-12-21T22:12:07","modified_gmt":"2022-12-22T03:12:07","slug":"iii-small-structural-matrix-completion-for-data-mining-applications","status":"publish","type":"research","link":"https:\/\/www.bu.edu\/cise\/research\/iii-small-structural-matrix-completion-for-data-mining-applications\/","title":{"rendered":"III: Small: Structural Matrix Completion for Data Mining Applications"},"content":{"rendered":"<p><span>A common problem arising in science and engineering is that a dataset may only be partially measured. Often the complete dataset is naturally expressed as a matrix &#8211; for example, traffic flows in a city, gene expression across a set of treatments, or ratings of movies for users. Recently, a new solution strategy has emerged for the problem of inferring the missing entries in such datasets, but the power and limits of this new &#8220;structural&#8221; approach are not fully understood as yet. This project will develop a better understanding of this structural approach and apply that understanding to a number of important problems. In addition, the project will develop new course materials for data science education, and train both graduate and undergraduate students.<\/span><\/p>\n<p><span>The matrix completion problem seeks to infer the missing entries of a matrix, under a low-rank assumption. To date, most matrix completion methods do not actually check whether the known entries contain sufficient information to complete the matrix. Recently, however, a new and very different class of &#8220;structural&#8221; methods have emerged, which analyze the information content of the visible matrix entries, and so can determine whether accurate completion is possible. From a data mining standpoint, the implications of structural matrix completion methods are largely unexplored. This project will investigate how to leverage structural matrix completion methods to attack a host of data analysis problems, including developing new methods for active matrix completion, new approaches to cross-validating matrix completion results, and new strategies for general matrix completion.<\/span><\/p>\n<p>For more information, click <a href=\"https:\/\/www.nsf.gov\/awardsearch\/showAward?AWD_ID=1421759&amp;HistoricalAwards=false\" target=\"_blank\" rel=\"noopener noreferrer\">here<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A common problem arising in science and engineering is that a dataset may only be partially measured. Often the complete dataset is naturally expressed as a matrix &#8211; for example, traffic flows in a city, gene expression across a set of treatments, or ratings of movies for users. Recently, a new solution strategy has emerged [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","format":"standard","_links":{"self":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/research\/37827"}],"collection":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/research"}],"about":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/types\/research"}],"version-history":[{"count":1,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/research\/37827\/revisions"}],"predecessor-version":[{"id":37828,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/research\/37827\/revisions\/37828"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/media?parent=37827"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}