In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Approximation structuring clustering is an extension of what is usually called square-error clustering" onto various cluster structures and data formats. It appears to be not...
: The aim of this paper is to revisit the phlogiston theory to see what can be learned from it about the relationship between scientific realism, approximate truth and successful r...
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...