Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
The FaCT (Fact and Concept Training) System provides a general platform for delivering practice in the form of discrete flashcard-like drills. The system optimizes practice schedu...
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...