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Efficient learning of smooth probability functions from Bernoulli tests with guarantees

By Paul Rolland and others
We study the fundamental problem of learning an unknown, smooth probability function via point-wise Bernoulli tests. We provide the first scalable algorithm for efficiently solving this problem with rigorous guarantees. In particular, we prove the convergence rate of our posterior update rule to the true probability function in L2-norm. Moreover,... Show more
January 7, 2019
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Efficient learning of smooth probability functions from Bernoulli tests with guarantees
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