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Composite Kernel Learning

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Detection of curvilinear structures has long been of interest due to its wide range of applications. Large amounts of imaging data could be readily used in many fields, but it is practically not possible to analyze them manually. Hence, the need for automa ...

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Whether it occurs in artificial or biological substrates, {\it learning} is a {distributed} phenomenon in at least two aspects. First, meaningful data and experiences are rarely found in one location, hence {\it learners} have a strong incentive to work to ...

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Learning is a complex, mostly invisible process that happens across spaces, occurring in the physical world but also increasingly in virtual worlds or web-based spaces. In order to explore what happens in such blended learning experience, there is a need ...

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In this paper, we consider the problem of sequentially optimizing a black-box function

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based on noisy samples and bandit feedback. We assume that

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is smooth in the sense of having a bounded norm in some reproducing kernel Hilbert space (RKHS), yield ...

2017