We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Relational reinforcement learning (RRL) is both a young and an old eld. In this paper, we trace the history of the eld to related disciplines, outline some current work and promis...
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
User generated content is extremely valuable for mining market intelligence because it is unsolicited. We study the problem of analyzing users' sentiment and opinion in their...
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...