Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
The problem of stochastic robust sum mean square error (MSE) minimization transceiver design is addressed for multiple-input multiple-output (MIMO) broadcast channels (BCs). The t...
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Abstract--Following the discovery of a fundamental connection between information measures and estimation measures in Gaussian channels, this paper explores the counterpart of thos...