We present Minimum Bayes-Risk word alignment for machine translation. This statistical, model-based approach attempts to minimize the expected risk of alignment errors under loss functions that measure alignment quality. We describe various loss functions, including some that incorporate linguistic analysis as can be obtained from parse trees, and show that these approaches can improve alignmen...

We propose a PAC-Bayes theorem for the sample-compression setting where each classifier is described by a compression subset of the training data and a message string of additional information. This setting, which is the appropriate one to describe many learning algorithms, strictly generalizes the usual data-independent setting where classifiers are represented only by data-independent message...

Bayesian hypothesis testing inevitably requires prior probabilities of hypotheses. Motivated by human decision makers, this thesis studies how binary decision making is performed when the decision-making agents use imperfect prior probabilities. Three detection models with multiple agents are investigated: distributed detection with symmetric fusion, sequential detection with social learning, a...

In this paper we introduce a natural image prior that directly represents a Gaussiansmoothed version of the natural image distribution. We include our prior in a formulation of image restoration as a Bayes estimator that also allows us to solve noise-blind image restoration problems. We show that the gradient of our prior corresponds to the mean-shift vector on the natural image distribution. I...

In diesem Artikel wird ein Vorschlag zur Berechnung eines technical-Value at Risk (t-VaR) diskutiert. Dieser Vorschlag basiert auf der Risikoszenarientechnik und verwendet die bedingte Wahrscheinlichkeit gemäß Bayes. Zur Ermittlung der Bedrohungen werden Angriffsbäume und Angriffsprofile eingesetzt. Die Schwachstellen sind empirisch für eine Versicherung im Jahr 2012 ermittelt worden. Die Angri...

COVID-19 is a global pandemic that requires coordinated response in all healthcare and national systems. Identifying patients at high risk of contracting the virus crucial to increasing awareness before become further infected by virus, which can cause severe respiratory illnesses requiring specialized care intensive units (ICUs). This study aims predict need for ICUs with virus. The predicted ...