[Colloquium] REMINDER: 10/5 TTIC Colloquium: Chandrajit Bajaj; University of Texas at Austin

[Mary Marre]

When:     Monday, October 5th at 11:00 a.m.

Where:    TTIC, 6045 S Kenwood Avenue, 5th Floor, Room 526

Speaker:  Chandrajit Bajaj; University of Texas at Austin

Title:  Fast, Approximate and Scalable Geometric Optimization


Abstract: Geometric optimization is the computational reduction technique
of choice for a wide variety of model selection and ranking problems (e.g.
drug screening with affinity ranking). Moreover, optimization occurs
naturally for solutions to rigid and flexible geometric shape similarity,
complementarity matching problems (e.g. predicting multi-component
assemblies, disaster reconstructions etc) . The optimization functional is
often a multi-dimensional correlation integral while the search space is
the product of transformations groups with dimension growth exponential in
the number of movable components (e.g. O(3^n) for an n-residue torsionally
flexible molecule ). In this talk, I shall dwell on solution of geometric
optimization methods that combat the curse of high dimensionality (e.g.via
the Johnson-Lindenstrauss lemma), and also achieve adequate tradeoffs
between speed and accuracy. Fast approximate estimations to the geometric
similarity or complementarity matching optimization problem take advantage
of a new scheme of generating low-discrepancy samplings of the n- product
configuration spaces, as well as utilization of approximate non-uniform
fast Fourier transforms. The geometric optimization functionals are in most
cases non-convex but tight probabilistic Azuma-Hoeffding inequalities can
be proved. A similar idea can be used to bound the prediction uncertainty
arising from uncertain input coordinates. Furthermore the numerical
approximation error of multi-dimensional convolution integrals can be
tightly bounded by using suitable reproducing kernel Hilbert spaces.

Bio: Chandrajit Bajaj is a Professor of Computer Science, and the director
of the Center for Computational Visualization in the Institute for
Computational and Engineering Sciences (ICES) at the University of Texas at
Austin. Bajaj holds the Computational Applied Mathematics Chair in
Visualization. He is also an affiliate faculty member of Mathematics,
Bio-medical Engineering, the Institute of Cell and Molecular Biology and
Neurosciences. He currently serves on the editorial boards for the
International Journal of Computational Geometry and Applications, and the
ACM Computing Surveys. He is a fellow of the American Association for the
Advancement of Science (AAAS), the Association of Computing Machinery
(ACM), and the Institute of Electrical and Electronic Engineers (IEEE).


*Hosts:* Jinbo Xu and Qixing Huang


For more information on the colloquium series or to subscribe to the
mailing list, please see http://www.ttic.edu/colloquium.php





Mary C. Marre
Administrative Assistant
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 504*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*
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