Reduced rank regression (RRR) has found application in various fields of signal processing. In this paper we propose a novel extension of the RRR model which we call sparse varia...
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
— We address the problem of energy efficient sensing by adaptively coordinating the sleep schedules of sensor nodes while guaranteeing that values of sleeping nodes can be recov...
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Automated facial expression recognition has received increased attention over the past two decades. Existing works in the field usually do not encode either the temporal evolutio...