Aim of this paper is to address the problem of learning Boolean functions from training data with missing values. We present an extension of the BRAIN algorithm, called U-BRAIN (U...
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
This paper presents a SVM-based prediction approach for constructing personal recommendation system for TV programs. We have applied Support Vector Machine (SVM) to personal predi...
In this paper we present a mechanism for translating information in heterogeneous digital library environments. We model information as a set of conjunctive constraints that are s...