---------- Forwarded message ----------
From: Christina Rohm <cr2
...@columbia.edu>
Date: Tue, Oct 16, 2012 at 10:51 AM
Subject: 10/18, 10 AM, 214 Mudd: Cosma Shalizi
To:
10:00 am Thursday Oct 18
rm 214 Mudd
Cosma Shalizi
Department of Statistics
CMU
Title:
LICORS: Light Cone Reconstruction of States for Non-parametric
Forecasting of Spatiotemporal Processes
Abstract:
We present a new, non-parametric forecasting method for data
where continuous values are observed discretely in space and time. Our
method, "light-cone reconstruction of states" (LICORS), uses physical
principles to identify predictive states which are local properties of
the system, both in space and time. LICORS discovers the number of
predictive states and their predictive distributions automatically,
and consistently, under mild assumptions on the data source. This
leads to a natural measure of local predictive complexity, which can
be used for automatic pattern discovery. Our work provides applied
researchers with a new, highly automatic method to analyze and
forecast spatio-temporal data. (Joint work with Georg Goerg;
http://arxiv.org/abs/1206.2398)
