Learning a tree-structured Ising model in order to make predictions
نویسندگان
چکیده
منابع مشابه
Learning a Tree-Structured Ising Model in Order to Make Predictions
We study the problem of learning a tree graphical model from samples such that low-order marginals are accurate. We define a distance (“small set TV” or ssTV) between distributions P and Q by taking the maximum, over all subsets S of a given size, of the total variation between the marginals of P and Q on S. Approximating a distribution to within small ssTV allows making predictions based on pa...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2020
ISSN: 0090-5364
DOI: 10.1214/19-aos1808