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Kernel Mean Embeddings

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Jiri Hron; Adam Scibior
Thursday 16 March 2017, 13:30-15:00
Engineering Department, CBL Room 438.

If you have a question about this talk, please contact Alessandro Davide Ialongo .

This talk will offer a general introduction to Kernel Mean Embeddings of distributions as well as a more in-depth treatment of Maximum Mean Discrepancy and Kernel Bayes’ Rule.

No reading is required, but for those interested here’s a good review article: https://arxiv.org/abs/1605.09522

This talk is part of the Machine Learning Reading Group @ CUED series.

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Abstract

This talk will offer a general introduction to Kernel Mean Embeddings of distributions as well as a more in-depth treatment of Maximum Mean Discrepancy and Kernel Bayes’ Rule.

No reading is required, but for those interested here’s a good review article: https://arxiv.org/abs/1605.09522

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