Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...
In this paper, we propose a model for representing and predicting distances in large-scale networks by matrix factorization. The model is useful for network distance sensitive app...
The Context Modelling Language (CML), derived from Object Role Modeling (ORM), is a powerful approach for capturing the pertinent object types and relationships between those type...
Abstract—Putative brain processes responsible for understanding language are based on spreading activation in semantic networks, providing enhanced representations that involve c...
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...