Model selection in unsupervised learning is a hard problem. In this paper a simple selection criterion for hyperparameters in one-class classifiers (OCCs) is proposed. It makes us...
We present a new blind deconvolution method for video sequence. It is derived following an inverse problem approach in a Bayesian framework. This method exploits the temporal cont...
Ferreol Soulez, Eric Thiebaut, Yves Tourneur, Alai...
The control of quantum phenomena is a topic that has carried out many challenging problems. Among others, the Hamiltonian identification, i.e, the inverse problem associated with ...
Constructive learning algorithms offer an attractive approach for the incremental construction of near-minimal neural-network architectures for pattern classification. They help ov...
Traditional Naive Bayes Classifier performs miserably on web-scale taxonomies. In this paper, we investigate the reasons behind such bad performance. We discover that the low perf...