Over the last years many statistical models have been proposed to restore tomographical images. However, their use in medical environment has been limited due to several factors. ...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...
Abstract. We propose a hierarchical process for inferring the 3D pose of a person from monocular images. First we infer a learned view-based 2D body model from a single image using...