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...
In this paper, we propose a novel semi-supervised speaker identification method that can alleviate the influence of nonstationarity such as session dependent variation, the reco...
This paper addresses the task of trajectory cost prediction, a new learning task for trajectories. The goal of this task is to predict the cost for an arbitrary (possibly unknown)...
Regression analysis is a powerful tool for the study of changes in a dependent variable as a function of an independent regressor variable, and in particular it is applicable to t...
Bradley C. Davis, P. Thomas Fletcher, Elizabeth Bu...
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...