Machine Learning in Ecosystem Informatics and Sustainability
introducer: Carlos Guestrin, Computer Science Department, Carnegie Mellon University
published: July 22, 2009, recorded: July 2009, views: 5217
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Ecosystem Informatics brings together mathematical and computational tools to address scientific and policy challenges in the ecosystem sciences. These challenges include novel sensors for collecting data, algorithms for automated data cleaning, learning methods for building statistical models from data and for fitting mechanistic models to data, and algorithms for designing optimal policies for biosphere management. This talk will describe recent work on the first two of these---new devices for automated arthropod population counting and linear Gaussian DBNs for automated cleaning of sensor network data. It will also give examples of open problems along the whole spectrum from sensors to policies.
Download slides: ijcai09_dietterich_mleis_01.ppt (16.8 MB)
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