The introduction of internet auction has significantly widened the pool of consumers who participate in auctions and increased the number of companies attempting to sell their products in an auction format. Previous empirical research on auctions has focused almost exclusively on the behavior of professional bidders. In this study, we collect data on a large number of internet auctions to explo...

Calculations of sensitivities of future experiments are a necessary ingredient in experimental high energy physics. Especially in the context of measurements of the neutrino oscillation parameters extensive studies are performed to arrive at the optimal configuration. In this note we clarify the definition of sensitivity as often applied in these studies. In addition we examine two of the most ...

Applying state of the art deeplearning models to novel real world datasets gives a practical evaluation of the generalizability of these models. Of importance in this process is how sensitive the hyper parameters of such models are to novel datasets as this would affect the reproducibility of a model. We present work to characterize the hyper parameter space of an LSTM for language modeling on ...

In his elegant discussion, Sripada distinguishes three possible innate bases for aspects of morality: (1) certain specific principles might be innate, (2) a less simple “principles and parameters” model might apply, and (3) innate biases might have have some influence over what morality a person acquires without determining the content of that morality.1 He argues against (1) and (2) and in fav...

The use of auctions for distributing resources in competing environments has produced a large variety of auctions types and algorithms to treat them. However, auctions have some problems when faced with some real-world applications containing renewable and perishable resources. In this paper we present a mechanism to deal with such issues by dynamically configuring some of the auction parameter...

When modeling student learning, tutors that use the Knowledge Tracing framework often assume that all students have the same set of model parameters. We find that when fitting parameters to individual students, there is significant variation among the individual’s parameters. We examine if this variation is important in terms of instructional decisions by computing the difference in the expecte...

Abstract. MAP estimators and HPD credible sets are often criticized in the literature because of paradoxical behaviour due to a lack of invariance under reparametrization. In this paper, we propose a new version of MAP estimators and HPD credible sets that avoid this undesirable feature. Moreover, in the special case of non-informative prior, the new MAP estimators coincide with the invariant f...