[colloquium] PICASso Talk for Coloquium news

[Sandy Barbu]

** PICASso:
** Program in Integrative Information, Computer and Application Sciences
** www.cs.princeton.edu/picasso
** Wednesday, October 26, 2005

Computation and Data Analysis in Biology and Information Sciences
www.cs.princeton.edu/picasso?bio_info_lunch.html

TITLE:	A Maximum Entropy Approach to Species Distribution Modeling
SPEAKER:	Miroslav Dudik, Department of Computer Science, Princeton
University
TIME:	  	Seminar begins at 12:30 p.m. (lunch provided 12:20)
LOCATION:	Room 402, Computer Science, Princeton University

ABSTRACT:
Species distribution modeling is an important problem in ecology and
conservation biology. In this problem, we are given a list of locations
where a species was observed and a set of environmental variables for the
region interest, e.g. elevation, soil type and annual rainfall. Based on
these, we would like to predict which conditions are favored by the species.
Two main challenges for machine learning are the small number of occurrence
localities and a lack of information where the species was NOT found
(negative examples). To address both of these in a statistically sound
manner, we propose to use the maximum entropy approach.

In this talk, we describe the maximum entropy principle (maxent) and how it
relates to the maximum likelihood. We describe a relaxation of maxent that
gives rise to non-asymptotic performance guarantees which depend very
moderately on the number or complexity of environmental variables. We also
present a novel coordinate descent algorithm for computing maxent models.
Finally, we mention how maxent can be used to address the problem of sample
selection bias.