We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eï¬...
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...
Abstract. Both fuzzy set theory and rough set theory play an important role in data-driven, systems modelling and analysis. They have been successfully applied to building various ...
In this paper, we propose a new variant of Latent Dirichlet Allocation(LDA): Collective LDA (C-LDA), for multiple corpora modeling. C-LDA combines multiple corpora during learning...