Santa Clara University

Mathematics and Computer Science department

Colloquium Series

Fall 2015

Unless otherwise noted, talks will be at 3:50 PM in O'Connor 104.  Also, there will be refreshments before each talk in O'Connor 31 at 3:40 PM.



 

Tuesday, 13 October

Speaker:  Abraham Martin del Campo, Institute of Science and Technology Austria


Title:  TBA

 

Abstract:  TBA

 




  Tuesday, 20 October

Speaker:  Abel Rodriguez, UC Santa Cruz


Title:  TBA

 

Abstract:  TBA  

 


 


Tuesday, 27 October

Speaker:  Matthew Johnston, San Jose State University


Title:  TBA

Abstract:  TBA

 




 

 

Tuesday, 10 November

Speaker:  Jordan Schettler, San Jose State University


Title:  TBA

 

Abstract:  TBA

 




 


 

SPRING 2015

 

Tuesday, 14 April

Speaker: Elizabeth Gross, San Jose State University


Title:  Goodness-of-fit testing for network models

 


Abstract:  When using statistical models for network data, we would like to know the goodness-of-fit of the model (i.e., how well the model fits the data).  This question has proved particularly challenging even for relatively simple classes of network models, as it currently requires sampling graphs with the same sufficient statistics (e.g., number of edges, number of triangles, degree sequence, etc) as the observed network.  In this talk, we will introduce statistical network models and present a method for goodness-of-fit testing for log-linear network models that is rooted in computational algebraic geometry. We will demonstrate the approach on the Holland-Leinhardt p_1 model for random directed graphs. This is joint work with Sonja Petrovic and Despina Stasi.





 








Tuesday, 28 April

Speaker:  Matthew Holmes, Undergraduate student at Santa Clara University


Title:  Enumerating Primitive Words and Images

 

Abstract:  Primitive words are strings that are not repetitions of some simpler substrings. For example, the string 101010 is not primitive, while the string 10000 is. In this work, I will explain how to generalize this notion to rectangular images and prove a formula based on the Mobius function for counting the number of primitive images of dimensions (m x n) over an alphabet of size k.  I will also discuss some upper and lower bounds for these formulas.

 

 

 

 




Tuesday, 5 May

Speaker: Richard Scott, Santa Clara University


Title: Cube complexes and generating functions

*** A Pi Mu Epsilon Sponsored Event 

 

Abstract:  Some of your favorite geometric objects can actually be constructed by gluing together cubes of various dimensions along their faces. A very useful way to study the topology of such an object is to pass to an infinite version called the "universal cover"which retains the original local geometry. In this talk we will partition the (infinitely many) vertices in the universal cover in such a way that we can count them. The result of this count is a generating function, the likes of which which you may have encountered in a combinatorics class. After computing a couple of these, we will connect topological properties of the original geometric object to algebraic properties of this generating function. I promise at least six pictures, at least three colors, at least two theorems, and at most one proof. 

 Scottimage

 








Tuesday, 26 May

Speaker:  Jeff Calder, UC Berkeley


Title: Partial differential equations and continuum limits for discrete sorting problems

 


Abstract:   Many problems in science and engineering involve the sorting, or ordering, of large amounts of data. A common sorting technique is to arrange the data into layers by repeatedly removing extremal points. Different definitions of extremality lead to different sorting algorithms. Two common examples are non-dominate sorting, and convex hull ordering, which are widely used in multi-objective optimization, machine learning, and robust statistics. Furthermore, non-dominated sorting is equivalent to the longest chain problem, and polynuclear growth, which are important problems in probability and combinatorics. In this talk, I will present some recent work showing that the layers obtained by sorting i.i.d. random variables converge almost surely in the large sample size limit to the level sets of a function that satisfies a partial differential equations (PDE). These PDE continuum limits open the door to very fast approximate sorting algorithms based on solving the PDE in place of the discrete sorting problem. I will give some applications of our work along these lines.

 

 

 





 

If you have a disability and require a reasonable accommodation,
please call/email Rick Scott 408-554-4460/rscott at scu dot edu (or
use 1-800-735-2929 TTY—California Relay).

Abstracts of previous talks are available here.
Printer-friendly format