Learning Ising Models with Independent Failures

COLT, pp. 1449-1469, 2019.

Cited by: 6|Bibtex|Views10|Links
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Abstract:

give the first efficient algorithm for learning the structure of an Ising model that tolerates independent failures; that is, each entry of the observed sample is missing with some unknown probability p. Our algorithm matches the essentially optimal runtime and sample complexity bounds of recent work for learning Ising models due to Kliv...More

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