Machine learning with quantum relative entropy
نویسندگان
چکیده
منابع مشابه
Cos 511: Theoretical Machine Learning 2 Relative Entropy and Chernoff Bounds 2.1 Relative Entropy
In the previous lecture, we saw that PAC learning is not enough to model real learning problems. We may not desire or even may not be able to find a hypothesis that is consistent with the training data. So we introduced a more general model in which the data is generated as a pair (x, y) from an unknown distribution D. And we defined the generalization error to be errD(h) = Pr(x,y)∼D[h(x) 6= y]...
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2009
ISSN: 1742-6596
DOI: 10.1088/1742-6596/143/1/012021