Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
This paper describes a fast, automated technique for accurate on-line estimation of the performance and power consumption of interacting processes in a multi-programmed, multi-cor...
Xi Chen, Chi Xu, Robert P. Dick, Zhuoqing Morley M...
Functional mixed-effects models are very useful in analyzing functional data. A general functional mixed-effects model that inherits the flexibility of linear mixed-effects model...
The Active Appearance Model (AAM) provides an efficient method for localizing objects that vary in both shape and texture, and uses a linear regressor to predict updates to model ...
Philip A. Tresadern, Patrick Sauer, Timothy F. Coo...
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...