Un of Tenn | Math Department

Seminars and Colloquiums
for the week of April 15 2013

Speakers:

Prof. Xiaopeng Zhao, UT Biomedical Engineering, Wednesday
Mr. Kyle Austin, Thursday
Prof. Ioannis Schizas - Univ. of TX - Arlington, Friday

*** Tea Time this week will be Monday - Wednesday at 3:00 pm.
Hosted this week by Ashley Rand. Everyone is welcome! ***

WEDNESDAY, April 17

MATH BIOLOGY SEMINAR
TIME: 12:20-1:10 p.m.
ROOM: Ayres 114
SPEAKER: Prof. Xiaopeng Zhao, UT Biomedical Engineering
TITLE: Nonlinear Dynamics in Physiology and Medicine (continued chapter 5 of this book)

ANALYSIS SEMINAR
TIME: 3:35
ROOM: Ayres 114
SPEAKER: Prof. Remus Nicoara
TITLE: Non-conjugate actionsof groups on von Neumann algebras (continued).
ABSTRACT: We will first review some known results about groups acting on von Neumann algebras. We will then construct certain parametric classes of non-conjugate actions on the hyperfinite II_1 factor

THURSDAY, April 18

ORAL SPECIALTY EXAM
TIME: 2:00 p.m.
ROOM: Ayres 114
SPEAKER: Mr. Kyle Austin
Committee: Professors Dydak (chair), Brodskiy, and Thistlethwaite.

FRIDAY, April 19

COLLOQUIUM
TIME: 3:30 p.m.
ROOM: Ayres 405
SPEAKER: Prof. Ioannis Schizas - Univ. of TX - Arlington
HOST: Prof. V. Maroulas
TITLE: Distributed Determination of Informative Network Nodes via
Sparsity-Cognizant Covariance Decomposition
ABSTRACT: Covariance matrices that consist of sparse factors arise in settings where the field sensed by a sensor network is formed by localized sources. In this presentation, it is shown that the task of identifying source-informative sensors boils down to estimating the support of the sparse covariance factors. Further, a novel distributed sparsity-aware matrix decomposition framework is derived to recover the support of the sparse factors of a matrix. The proposed framework relies on norm-one regularization and the notion of missing covariance entries. The associated minimization problems are solved using computationally efficient coordinate descent iterations combined with matrix deflation mechanisms. A simple scheme is also developed to set appropriately the sparsity-adjusting coefficients. The distributed framework can provably recover the support of the covariance factors when field sources do not overlap, while each subset of sensors sensing a specific source forms a connected communication graph.

If you are interested in giving or arranging a talk for one of our seminars or colloquiums,
please review our calendar.

If you have questions, or a date you would like to confirm, please contact colloquium AT math DOT utk DOT edu

Past notices:

spring break