Connectionists: Graduate Summer School at UCLA's Institute for Pure and Applied Mathematics

[Tina Eliassi-Rad]

Institute for Pure & Applied Mathematics (IPAM)
University of California, Los Angeles

Graduate Summer School: Intelligent Extraction of Information from Graphs
and High Dimensional Data

July 11-29, 2005

http://www.ipam.ucla.edu/programs/gss2005/

In recent years, there has been a rapidly increasing demand for targeted
analysis of large data streams and large networks. One of the main goals
has been identification of key features: face recognition in video streams
and voice recognition in audio streams are two examples. Another goal has
been inference of relationships: pattern discovery in large databases and
determination of key links in social networks. At the same time, a number
of scientific disciplines have come together to develop a theory for the
analysis of high-dimensional data, as well as for the analysis of dynamic
processes on massive graphs. The new techniques and new mathematics coming
out of this line of research are ideally suited to a wide range of
applications.

Applications and connections to real challenges will be drawn from: data
fusion, automated feature extraction, face and shape recognition, spectral
and hyperspectral image analysis, relational data mining, link analysis
and discovery, graph mining, social and transactional networks, robust
network design (making networks hard to break), optimal epidemic
intervention (making networks easy to break), and hidden state inference
(where are targets based on indirect measurements?).

The summer school is intended for graduate students and postdocs, as well
as more senior researchers interested in focusing their efforts on these
mathematical challenges and crucial applications. The program is organized
as follows.

Week 1: High-dimensional data, relational data and kernel methods.
Week 2: Image analysis and machine learning.
Week 3: Streaming data and networks.

We anticipate that some participants will be interested in attending the
entire program while others will want to stay for only one or two of the
week-long sessions.

Speakers

James Abello (Rutgers University)
Uri Alon (Weizmann Institute)
Tom Asaki (Los Alamos National Laboratory)
Erik Bollt (Clarkson University)
Leon Bottou (NEC)
Robert Burleson (Lawrence Livermore National Laboratory)
Frdric Cao (IRISA)
Rick Chartrand (Los Alamos National Laboratory)
Ronald Coifman (Yale University)
John Conroy (Institute for Defense Analysis)
Terence Critchlow (Lawrence Livermore National Laboratory)
George Cybenko (Dartmouth University)
David Donoho (Stanford University)
Tina Eliassi-Rad (Lawrence Livermore National Laboratory)
Christos Faloutsos (Carnegie Mellon University)
Leslie Greengard (New York University/Courant Institute of Mathematical
Sciences)
Dennis Healy (DARPA)
Martial Hebert (Carnegie Mellon University)
David Heckerman (Microsoft Research)
Piotr Indyk (Massachusetts Institute of Technology)
Peter Jones (Yale University)
Michael Jordan (University of California at Berkeley)
Ron Kimmel (Technion, Haifa, Israel)
Daphne Koller (Stanford University)
John Lafferty (Carnegie Mellon University)
Yann LeCun (New York University)
Gilad Lerman (University of Minnesota)
Mehryar Mohri (New York University)
Andrew Moore (Carnegie Mellon University)
Jean-Michel Morel (Ecole Normale Suprieure, Cachan, France)
Robert Nowak (University of Wisconsin)
Bruno Olshausen (University of California at Davis)
Stanley Osher (IPAM)
Carey Priebe (Johns Hopkins University)
Prabhakar Raghavan (Verity, Inc. and Stanford University)
Ronald Resmini (NGA)
Guillermo Sapiro (University of Minnesota)
Lawrence Saul (University of Pennsylvania)
Edward Scheinerman (Johns Hopkins University)
Larry Schultz (Los Alamos National Laboratory)
Ingo Steinwart (Los Alamos National Laboratory)
William Szewczyk (NCSC)
Demetri Terzopoulos (New York University)
James Theiler (Los Alamos National Laboratory)
Godfried Toussaint (McGill University)
Richard Tsai (Princeton University)
Kevin Vixie (Los Alamos National Laboratory)
Grace Wahba (University of Wisconsin)