We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Maximum likelihood (ML) is increasingly used as an optimality criterion for selecting evolutionary trees, but finding the global optimum is a hard computational task. Because no g...
We address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new Expectation-Maximization (EM) scheme to impose both spatia...
As the d esig n-m anu factu ring interface becom es increasing ly com plicated with IC technolog y scaling , the correspond ing process variability poses g reat challeng es for na...
Yang Xu, Kan-Lin Hsiung, Xin Li, Ivan Nausieda, St...
We describe a clustering algorithm based on continuous Hidden Markov Models (HMM) to automatically classify both electrocardiogram (ECG) and intracranial pressure (ICP) beats base...