Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-...
Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...