Sparse representations of signals have received a great deal of attention in recent years, and the sparse representation classifier has very lately appeared in a speaker recogniti...
Jia Min Karen Kua, Eliathamby Ambikairajah, Julien...
In this paper, we propose to apply sparse canonical correlation analysis (sparse CCA) to an important genome-wide association study problem, eQTL mapping. Existing sparse CCA mode...
Here we present a scalable method to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connec...
Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Ra...
Fourier Transform Infrared (FT-IR) spectroscopic imaging is a potentially valuable tool for diagnosing breast and prostate cancer, but its clinical deployment is limited due to lo...
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...