Methods for imputation of missing data in the so-called least-squares approximation approach, a non-parametric computationally efficient multidimensional technique, are experiment...
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
We present a pipelining, dynamically usercontrollable reorder operator, for use in dataintensive applications. Allowing the user to reorder the data delivery on the fly increases...
Vijayshankar Raman, Bhaskaran Raman, Joseph M. Hel...
— Recent advances have demonstrated the potential benefits of coordinated management of thermal load in data centers, including reduced cooling costs and improved resistance to ...
Justin D. Moore, Jeffrey S. Chase, Parthasarathy R...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...