Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Modern object-relational database systems are capable of managing multimedia data, e.g. image, video and audio. In this paper we study how such universal database systems can be u...
Text is a pervasive information type, and many applications require querying over text sources in addition to structured data. This paper studies the problem of query processing i...
We describe an architecture for representing and managing context shifts that supports dynamic data interpretation. This architecture utilizes two layers of learning and three lay...
Nikita A. Sakhanenko, George F. Luger, Carl R. Ste...
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...