Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
We utilize evolutionary game theory to study the evolution of cooperative societies and the behaviors of individual agents (i.e., players) in such societies. We present a novel pla...
Kan-Leung Cheng, Inon Zuckerman, Ugur Kuter, Dana ...
As planning agents grow more sophisticated, issues of plan representation arise alongside concerns with plan generation. Planning methods work over increasingly large and difficul...
Recent work has shown promise in using large, publicly available, hand-contributed commonsense databases as joint models that can be used to infer human state from day-to-day sens...
William Pentney, Matthai Philipose, Jeff A. Bilmes...
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...