Search results for "Probability"
showing 10 items of 3417 documents
Pragmatic languages with universal grammars
2012
Abstract This paper constructs the equilibrium for a specific code that can be seen as a “universal grammar” in a class of common interest Sender–Receiver games where players communicate through a noisy channel. We propose a Senderʼs signaling strategy which does not depend on either the game payoffs or the initial probability distribution. The Receiverʼs strategy partitions the set of possible sequences into subsets, with a single action assignment to each of them. The Senderʼs signaling strategy is a Nash equilibrium, i.e. when the Receiver responds best to the Senderʼs strategy, the Sender has no incentive to deviate. An example shows that a tie-breaking decoding is crucial for the block…
Values of games with probabilistic graphs
1999
Abstract In this paper we consider games with probabilistic graphs. The model we develop is an extension of the model of games with communication restrictions by Myerson (1977) . In the Myerson model each pair of players is joined by a link in the graph if and only if these two players can communicate directly. The current paper considers a more general setting in which each pair of players has some probability of direct communication. The value is defined and characterized in this context. It is a natural extension of the Myerson value and it turns out to be the Shapley value of a modified game.
REPEATED GAMES WITH PROBABILISTIC HORIZON
2005
Repeated games with probabilistic horizon are defined as those games where players have a common probability structure over the length of the game's repetition, T. In particular, for each t, they assign a probability pt to the event that "the game ends in period t". In this framework we analyze Generalized Prisoners' Dilemma games in both finite stage and differentiable stage games. Our construction shows that it is possible to reach cooperative equilibria under some conditions on the distribution of the discrete random variable T even if the expected length of the game is finite. More precisely, we completely characterize the existence of sub-game perfect cooperative equilibria in finite s…
Thompson Sampling for Dynamic Multi-armed Bandits
2011
The importance of multi-armed bandit (MAB) problems is on the rise due to their recent application in a large variety of areas such as online advertising, news article selection, wireless networks, and medicinal trials, to name a few. The most common assumption made when solving such MAB problems is that the unknown reward probability theta k of each bandit arm k is fixed. However, this assumption rarely holds in practice simply because real-life problems often involve underlying processes that are dynamically evolving. In this paper, we model problems where reward probabilities theta k are drifting, and introduce a new method called Dynamic Thompson Sampling (DTS) that facilitates Order St…
Learning spatial filters for multispectral image segmentation.
2010
International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.
Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis.
2016
This study examined whether adolescents’ time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely t…
Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate va…
2017
The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear funct…
Dynamic graphics in Excel for teaching statistics: understanding the probability density function
2011
In this article, we show a dynamic graphic in Excel that is used to introduce an important concept in our subject, Statistics I: the probability density function. This interactive graphic seeks to facilitate conceptual understanding of the main aspects analysed by the learners.
Ranking-Oriented Collaborative Filtering: A Listwise Approach
2016
Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…
The effect of automated taxa identification errors on biological indices
2017
In benthic macroinvertebrate biomonitoring systems, the target is to determine the status of ecosystems based on several biological indices. To increase cost-efficiency, computer-based taxa identification for image data has recently been developed. Taxa identification errors can, however, have strong effects on the indices and thus on the determination of the ecological status. In order to shift the biomonitoring process towards automated expert systems, we need a clear understanding on the bias caused by automation. In this paper, we examine eleven classification methods in the case of macroinvertebrate image data and show how their classification errors propagate into different biological…