Image model plays a critical role in recovering diagnosis-relevant information from noisy observation data. Unlike conventional denoising techniques based on local models, a patch...
The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels shoul...
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
A dependent hierarchical beta process (dHBP) is developed as a prior for data that may be represented in terms of a sparse set of latent features (dictionary elements), with covar...
Abstract)",4th Annual Walter Lincoln Hawkins Research Conference, RPI, November 2005. B. Hill, \Correlated Caching for Correlated Data", 2nd Annual Walter Lincoln Hawkins...