Maximum Entropy and Species Distribution Modeling - 2007 - Lecture

Explore the application of maximum-entropy methods to species distribution modeling in this lecture by Rob Schapire from Princeton University. Delve into the critical problem of modeling geographic distributions of plant and animal species for conservation biology. Learn about the challenges of machine learning with limited positive examples and no negative examples. Discover how maximum-entropy techniques effectively address this issue, including a version with strong theoretical performance guarantees. Examine extensive experimental tests, surprising applications, and joint work with colleagues. Gain insights into habitat modeling, estimating Pi, relaxed methods, bounds, algorithms, and extensions. Understand the importance of this research for conservation efforts and threatened species protection.

Introduction
Problem Statement
Why Care
Challenges
Maximum entropy approach
Habitat modeling
Estimating Pi
Relaxed Method
Bounds
Algorithm
Extensions
Applications