The requirements of real-world data mining problems vary extensively. It is plausible to assume that some of these requirements can be expressed as application-specific performan...
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods we...
Creating more fine-grained annotated data than previously relevent document sets is important for evaluating individual components in automatic question answering systems. In this...
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...