The  Weizmann  Institute  of  Science
                  Faculty of Mathematics and Computer Science
                 Mathematical Analysis and Applications Seminar
                    Seminar Room, Room 261, Ziskind Building
                           on Tuesday, March 20, 2012
                                  11:00 - noon
                           Note the unusual location
                                  Nathan Kutz
                            University of Washington
                                 will speak on
               Data driven modeling and dimensionality reduction
Dimensionality reduction is a common method for rendering tractable a host of
problems arising in the physical, engineering and biological sciences. In
recent years, methods from data analysis have started playing critical roles in
more traditional applied mathematics problems typically analyzed with dynamical
systems and PDE techniques. In this talk, three  disparate examples will be
considered from (i) image processing, (ii) PDE solution techniques and (iii)
neuroscience. In each case, dimensionality reduction, typically achieved
through a principal component analysis (PCA) or orthogonal mode decomposition
(POD), i.e. a singular value decomposition, achieves remarkable success in
providing a mathematical framework which is much more amenable to analysis,
thus allowing for a better characterization of the physical, engineering or
biological system of interest.
Technion Math Net-2 (TECHMATH2)
Editor: Michael Cwikel   <> 
Announcement from: Yaeli Malka   <>