Subspace segmentation is the process of clustering a set of data points that are assumed to
lie on the union of multiple linear or affine subspaces, and is increasingly being recognized …

Conventional multi-task Bayesian compressive sensing methods, which compute the sparse
representations of signals with a group sparse pattern, generally ignore the inner sparse …

In this paper, we present a novel multimodal sparse dictionary learning algorithm based on
a hierarchical sparse Bayesian framework. The framework allows for enforcing joint sparsity …

In the problem of multiple support recovery, we are given access to linear measurements of
multiple sparse samples in. These samples can be partitioned into groups, with samples …

Real-time processing of physiological signals collected from wearable sensors that can be
done with low computational power is a requirement for continuous health monitoring. Such …

Throughout this supplementary file, equations from the main paper will be prefixed by an 'M',
eg,(M. 12) would denote equation (12) from the main paper. Regarding MTSC, the input is …