The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
Activity Number:
|
170
|
Type:
|
Contributed
|
Date/Time:
|
Monday, August 1, 2011 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Biometrics Section
|
Abstract - #301847 |
Title:
|
Estimating Networks with Jumps
|
Author(s):
|
Mladen Kolar*+ and Eric Poe Xing
|
Companies:
|
Carnegie Mellon University and Carnegie Mellon University
|
Address:
|
5000 Forbes Avenue, Pittsburgh, PA, , USA
|
Keywords:
|
Gaussian graphical models ;
network models ;
dynamic network models ;
high-dimensional inference ;
structural changes
|
Abstract:
|
We study the problem of estimating a temporally varying coefficient and varying structure graphical (VCVS) model underlying nonstationary time series data, such as social states of interacting individuals or microarray expression profiles of gene networks, as opposed to i.i.d. data from an invariant model widely considered in current literature of structural estimation. In particular, we consider the scenario in which the model evolves in a piece-wise constant fashion. We propose a procedure that minimizes the so-called TESLA loss (i.e., temporally smoothed L1 regularized regression), which allows jointly estimating the partition boundaries of the VCVS model and the coefficient of the sparse precision matrix on each block of the partition. A highly scalable proximal gradient method is proposed to solve the resultant convex optimization problem; and the conditions for sparsistent estimation and the convergence rate of both the partition boundaries and the network structure are established for the first time for such estimators.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2011 program
|
2011 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.