Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
We present a method for learning discriminative linear feature extraction using independent tasks. More concretely, given a target classification task, we consider a complementary...
STARI is a high-speed signaling technique that uses both synchronous and self-timed circuits. To demonstrate STARI, a chip has been fabricated using the MOSIS 2 CMOS process. In a...