Image classification is an important task in computer vision. However, how to assign suitable labels to images is a subjective matter, especially when some images can be categoriz...
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/traini...
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...