Imaging with highly incomplete and corrupted data

Exact Recovery of Chaotic Systems from Highly Corrupted Data

Learning the governing equations in dynamical systems from time-varying measurements is of great interest across different scientific fields. This task becomes prohibitive when such data is moreover highly corrupted, for example, due to the recording mechanism failing over unknown intervals of time. When the underlying system exhibits chaotic behavior, such as sensitivity to initial conditions,...

Image Reconstruction from Incomplete Data

Image Reconstruction from Incomplete Data

Fast greedy algorithm for subspace clustering from corrupted and incomplete data

We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces. The main difference of our algorithm from predecessors is its ability to work with noisy data having a high rate of erasures (missed entries with the known coordinates) and errors (corrupted entries with unknown...

Corrupted Speech Data Considered Useful

The success of Voice-over-IP technology will crucially depend on the provision of a certain level of perceptual speech quality. In this paper we demonstrate that keeping as much corrupted speech data as possible results in a major step towards this goal. To this end, we explore the combination of two key factors which influence the speech quality as perceived by the user: networking mechanisms ...