We present a Bayesian approach to color constancy which utilizes a nonGaussian probabilistic model of the image formation process. The parameters of this model are estimated direc...
Charles R. Rosenberg, Thomas P. Minka, Alok Ladsar...
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
—In this paper, we present a method to analyze different implementations of stream-based applications on heterogeneous multiprocessor systems. We take both resource usage and per...
— Calibration is the procedure of quantifying mechanical deficiencies of machines and compensating them by appropriate adjustment. This paper introduces a modelbased measurement...
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...