A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...
Applications in Computer Networks often require high throughput access to large data structures for lookup and classification. Many advanced algorithms exist to speed these searc...
This paper describes an efficient and robust approach to provide a safe execution environment for an entire operating system, such as Linux, and all its applications. The approach...
John Criswell, Andrew Lenharth, Dinakar Dhurjati, ...
This paper introduces a novel machine learning model called multiple instance ranking (MIRank) that enables ranking to be performed in a multiple instance learning setting. The mo...
Charles Bergeron, Jed Zaretzki, Curt M. Breneman, ...