Abstract. This paper presents a novel dynamically reconfigurable hardware architecture for lossless compression and its optimization for space imagery. The proposed system makes us...
This paper develops bounds on out-of-sample error rates for support vector machines (SVMs). The bounds are based on the numbers of support vectors in the SVMs rather than on VC di...
Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the r...
Ying Feng, Divyakant Agrawal, Amr El Abbadi, Ahmed...
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
Dynamical low-rank approximation is a differential-equation based approach to efficiently computing low-rank approximations to time-dependent large data matrices or to solutions o...