Department of

Mathematics

Seminar Calendar
for events the day of Friday, December 1, 2017.

.
events for the
events containing

Questions regarding events or the calendar should be directed to Tori Corkery.
    November 2017          December 2017           January 2018
Su Mo Tu We Th Fr Sa   Su Mo Tu We Th Fr Sa   Su Mo Tu We Th Fr Sa
1  2  3  4                   1  2       1  2  3  4  5  6
5  6  7  8  9 10 11    3  4  5  6  7  8  9    7  8  9 10 11 12 13
12 13 14 15 16 17 18   10 11 12 13 14 15 16   14 15 16 17 18 19 20
19 20 21 22 23 24 25   17 18 19 20 21 22 23   21 22 23 24 25 26 27
26 27 28 29 30         24 25 26 27 28 29 30   28 29 30 31
31


Friday, December 1, 2017

12:00 pm in 243 Altgeld Hall,Friday, December 1, 2017

Dynamical Systems via Machine Learning

Lan Wang (UIUC)

Abstract: Machine learning has become an important technique to understand and predict the trends of large volume of data. While most machine learning models are static, static is hardly the case in real life. We need to create dynamical models by generalizing from past experience and results. In this talk, I will explore the usages of dynamical systems in machine learning. The talk will be divided into two parts. First, I will focus on the Kalman filter, a famous Bayesian model permitting exact inference in a discrete dynamical system, and its extensions. Then, I will discuss how to use continuous dynamical systems as a tool for machine learning, especially for deep neural networks. Some of the results are from my previous internship experience.

3:00 pm in 343 Altgeld Hall,Friday, December 1, 2017

Equations of Kalman Varieties

Amy Huang (University of Wisconsin)

Abstract: Given a subspace L of a vector space V, the Kalman variety consists of all matrices of V that have a nonzero eigenvector in L. I will discuss how to apply Kempf Vanishing technique with some more explicit constructions to get a long exact sequence involving coordinate ring of Kalman variety, its normalization and some other related varieties in characteristic zero. Time permitting I will also discuss how to extract more information from the long exact sequence including the minimal defining equations for Kalman varieties.