Numerical Linear Algebra Methods in Data Mining

SpeakerDr. Yousef Saad
Organization University of Minnesota
LocationEBII 1230
DateJanuary 31, 2014 12:50 PM


The field of data mining is the source of many new, interesting, and sometimes challenging, linear algebra problems.  In fact, one can say that data mining and machine learning are now beginning to shape a "new chapter" in numerical linear algebra, replacing Computational Fluid Dynamics and PDEs as the main source of `model' problems in Numerical Linear Algebra. The talk will start with an overview of the key concepts and then discuss dimension reduction methods which play a major role. We will illustrate these concepts with a few applications, including information retrieval; face recognition and matrix completion for recommender systems. An important emerging application is `materials informatics’.  The synergy between high-performance computing, efficient electronic structure algorithms, and data mining, may potentially lead to major discoveries in materials.  We will report on our first experiments in `materials informatics', a methodology which blends data mining and materials science.


Yousef Saad is a college of Science and Technology distinguished professor with the department of computer science and engineering at the University of Minnesota.  He received the "Doctorat d'Etat" from the University of Grenoble (France) in 1983.  He joined the University of Minnesota in 1990 as a Professor of computer science and a Fellow of the Minnesota Supercomputer Institute.  He was head of the department of Computer Science and Engineering from January 1997 to June 2000, and became a CSE distinguished professor in 2005.  From 1981 to 1990, he held positions at the University of California at Berkeley, Yale, the University of Illinois, and the Research Institute for Advanced Computer Science (RIACS).  His current research interests include: numerical linear algebra, sparse matrix computations, iterative methods, parallel computing, numerical methods   for electronic structure, and data mining.   He is the author of two monographs and over 160 journal articles.  He is also the developer or co-developer of several software packages for solving sparse linear systems of equations including SPARSKIT, pARMS, and ITSOL. Yousef Saad is a SIAM fellow (class of 2010) and a fellow of the AAAS (2011).

  January 2014
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