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Showing 1 to 4 of 4 for “"Energy distance"”.
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Likelihood-Free Hypothesis Testing and Applications of the Energy Distance
… the key technical tool being a connection to the energy distance. In particular, we propose a density estimation routine based on minimizing the generalized energy distance, targeting smooth densities and Gaussian mixtures. We interpret our results in terms of half-space separability over these …
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Distribution distance measures in generative and privacy models
Distribution distance measures provide a useful class of tools for generative and privacy models. In both cases, the goal is to simulate a data distribution without revealing too much about individual points. While early generative models focused on matching data in a component-wise manner, the …
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Statistical inference for high-dimensional data
… proposed methods. In the first chapter, we study distance covariance, Hilbert-Schmidt covariance (aka Hilbert-Schmidt independence criterion [Gretton et al. (2008)] and related independence tests under the high dimensional scenario. We show that the sample distance/Hilbert-Schmidt covariance …
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Athermal photonic devices and circuits on a silicon platform
… as an eective solution that can offer cost, energy, distance and bandwidth density improvements over copper. Monolithic integration of optics and electronics has been enabled by silicon photonic devices that can be fabricated using CMOS technology. However, high levels of device integration …