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ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...

Abstract: We consider the problem of data association for multi-target tracking in the presence of an unknown number of targets. For this application, inference in models which place parametric priors ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

Abstract: We consider two examples of statistical inference for two related populations. In one example we characterize two patient populations that are relevant in the construction of a clinical ...

For whom? The events are open to all interested, within or outside of KI. The events are free of charge. The program is tailored towards users of statistics (but you don’t need to be a statistician), ...

In this paper, researchers from Queen Mary University of London, UK, University of Oxford, UK, Memorial University of Newfoundland, Canada, and Google DeepMind Moutain View, CA, USA proposed a ...

Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...

This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including ...

Copyright: © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Frequentist and Bayesian ...

The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which is very closely related to ...