HMM-based acoustic models built from bootstrap are generally very large, especially when full covariance matrices are used for Gaussians. Therefore, clustering is needed to compac...
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization an...
Constantinos Evangelinos, Pierre F. J. Lermusiaux,...
Traditional High Performance Computing systems require extensive management and suffer from security and configuration problems. This paper presents a new clustermanagement syste...
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...