Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the ...
Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Ja...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
DNA microarrays have gained widespread uses in biological studies. Missing values in a microarray experiment must be estimated before further analysis. In this paper, we propose a...
Abstract—The Sparse Matrix-Vector Multiplication kernel exhibits limited potential for taking advantage of modern shared memory architectures due to its large memory bandwidth re...
Kornilios Kourtis, Georgios I. Goumas, Nectarios K...
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...