Past Probability Seminars Spring 2020

From UW-Math Wiki
Revision as of 18:05, 15 December 2014 by Pmwood (talk | contribs)
Jump to navigation Jump to search
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.


Spring 2015

Thursdays in 901 Van Vleck Hall at 2:25 PM, unless otherwise noted.

If you would like to sign up for the email list to receive seminar announcements then please send an email to join-probsem@lists.wisc.edu.

Thursday, January 15, Miklos Racz, UC-Berkeley Stats

Title: TBA



Monday, December 1, Joe Neeman, UT-Austin, 4pm, Room B239 Van Vleck Hall

Please note the unusual time and room.

Title: Some phase transitions in the stochastic block model

Abstract: The stochastic block model is a random graph model that was originally 30 years ago to study community detection in networks. To generate a random graph from this model, begin with two classes of vertices and then connect each pair of vertices independently at random, with probability p if they are in the same class and probability q otherwise. Some questions come to mind: can we reconstruct the classes if we only observe the graph? What if we only want to partially reconstruct the classes? How different is this model from an Erdos-Renyi graph anyway? The answers to these questions depend on p and q, and we will say exactly how.

Thursday, December 4, Arjun Krishnan, Fields Institute

Title: Variational formula for the time-constant of first-passage percolation

Abstract: Consider first-passage percolation with positive, stationary-ergodic weights on the square lattice in d-dimensions. Let [math]\displaystyle{ T(x) }[/math] be the first-passage time from the origin to [math]\displaystyle{ x }[/math] in [math]\displaystyle{ Z^d }[/math]. The convergence of [math]\displaystyle{ T([nx])/n }[/math] to the time constant as [math]\displaystyle{ n }[/math] tends to infinity is a consequence of the subadditive ergodic theorem. This convergence can be viewed as a problem of homogenization for a discrete Hamilton-Jacobi-Bellman (HJB) equation. By borrowing several tools from the continuum theory of stochastic homogenization for HJB equations, we derive an exact variational formula (duality principle) for the time-constant. Under a symmetry assumption, we will use the variational formula to construct an explicit iteration that produces the limit shape.


-->

Past Seminars