Results 21 to 30 of about 294,457 (253)
Сравнительная политикаThis article endeavors to construct a composite indicator designed to facilitate the comparative assessment of institutional capacities across diverse political systems.
I. Ye. Gorelskiy
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, 2003 Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.
Alexander J. Smola, Bernhard Schölkopf
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Bayesian inference: more than Bayes’s theorem
Frontiers in Astronomy and Space SciencesBayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function.
Thomas J. Loredo, Robert L. Wolpert
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A Bayesian Method for Characterizing Population Heterogeneity
Games, 2019 A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity.
Dale O. Stahl
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A Bayesian Method Reexamined [PDF]
, 1994 Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)
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Model selection for the extraction of movement primitives
Frontiers in Computational Neuroscience, 2013 A wide range of blind source separation methods have been used in motor control research for the extraction of movement primitives from EMG and kinematic data.
Dominik M Endres +2 more
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Introducing Bayesian Analysis With m&m's®: An Active-Learning Exercise for Undergraduates
Journal of Statistics Education, 2019 We present an active-learning strategy for undergraduates that applies Bayesian analysis to candy-covered chocolate m&m’s®. The exercise is best suited for small class sizes and tutorial settings, after students have been introduced to the concepts of ...
Gwendolyn Eadie +3 more
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A Sequential Algorithm for Signal Segmentation
Entropy, 2018 The problem of event detection in general noisy signals arises in many applications; usually, either a functional form of the event is available, or a previous annotated sample with instances of the event that can be used to train a classification ...
Paulo Hubert +2 more
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Bayesian Computational Methods [PDF]
, 2011 In this chapter, we will first present the most standard computational challenges met in Bayesian Statistics, focussing primarily on mixture estimation and on model choice issues, and then relate these problems with computational solutions. Of course, this chapter is only a terse introduction to the problems and solutions related to Bayesian ...
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Bayesian Methods for Graph Clustering [PDF]
, 2009 Networks are used in many scientific fields such as biology, social science, and information technology. They aim at modelling, with edges, the way objects of interest, represented by vertices, are related to each other. Looking for clusters of vertices, also called communities or modules, has appeared to be a powerful approach for capturing the ...
Latouche, Pierre +2 more
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