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Generalized active learning and design of statistical experiments for manifold-valued data
Characterizing the appearance of real-world surfaces is a fundamental problem in multidimensional reflectometry, computer vision and computer graphics.
Unsupervised robust nonparametric learning of hidden community properties
We consider learning of fundamental properties of communities in large noisy networks, in the prototypical situation where the nodes or users are split into two classes according to a binary property, e. g., according to their opinions or preferences on a topic.
Unsupervised nonparametric detection of unknown objects in noisy images based on percolation theory
We develop an unsupervised, nonparametric, and scalable statistical learning method for detection of unknown objects in noisy images.
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