MCMC Learning

author: Varun Kanade, École normale supérieure Paris
published: Aug. 20, 2015,   recorded: July 2015,   views: 123
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Description

The theory of learning under the uniform distribution is rich and deep, with connections to cryptography, computational complexity, and the analysis of boolean functions to name a few areas. This theory however is very limited due to the fact that the uniform distribution and the corresponding Fourier basis are rarely encountered as a statistical model.

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Download slides icon Download slides: colt2015_kanade_mcmc_learning_01.pdf (803.3 KB)


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