Natural language research announcements

["Samdani, Rajhans" <rsamdan2 AT illinois.edu>]

Hi all,

This is a gentle reminder for today's talk by Prof. John Lafferty 
(http://www.cs.cmu.edu/~lafferty/) at the AIIS seminar 
(http://cogcomp.cs.illinois.edu/sites/aiis/). Please note that the talk venue 
is 2405 SC. Following are the details:

When:
Nov 9, Friday. 4 pm.

Where:
2405, Siebel Center

Title:
Graphical Model Estimation

Abstract:
The graphical model has proven to be a useful abstraction in
statistics and machine learning.  The starting point is the graph of a
distribution.  While often the graph is assumed given, we have been
studying the problem of estimating the graph from data.  In this talk
we present several nonparametric and semi-parametric methods for graph
estimation.  One approach is a nonparametric extension of the Gaussian
graphical model that allows arbitrary graphs.  For the discrete
Gaussian (Ising model), we use parallel neighborhood selection with
L1-regularized logistic regression.  Alternatively, we can restrict
the family of graphs to spanning forests, enabling the use of fully
nonparametric density estimation in high dimensions.  When additional
covariates are available, we propose a framework for graph-valued
regression.  The resulting methods are easy to understand and use,
theoretically well supported, and effective for modeling and exploring
high dimensional data.  Joint work with Han Liu, Pradeep Ravikumar,
Martin Wainwright, and Larry Wasserman.


Bio
John Lafferty is the Louis Block Professor in the Departments of
Statistics, Computer Science, and the College at The University of
Chicago. His research area is machine learning, with a focus on
computational and statistical aspects of nonparametric methods,
high-dimensional data, graphical models, and applications.  An
associate editor of the Journal of Machine Learning Research,
Dr. Lafferty served as program co-chair and general co-chair of the
Neural Information Processing Systems Foundation conferences in 2009
and 2010. Dr. Lafferty received his doctoral degree in mathematics
from Princeton University, where he was a member of the Program in
Applied and Computational Mathematics.  Prior to joining the
University of Chicago in 2011, he was Professor of Computer Science,
Machine Learning, and Statistics at Carnegie Mellon University, where
he is currently an Adjunct Professor.

Hoping to see you all there!
Best,
Rajhans