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- W328304115 abstract "We give an algorithm that with high probability properly learns random monotone DNF with t(n) terms of length ~logt(n) under the uniform distribution on the Boolean cube {0,1}^n. For any function t(n)@?poly(n) the algorithm runs in time poly(n,1/@e) and with high probability outputs an @e-accurate monotone DNF hypothesis. This is the first algorithm that can learn monotone DNF of arbitrary polynomial size in a reasonable average-case model of learning from random examples only. Our approach relies on the discovery and application of new Fourier properties of monotone functions which may be of independent interest." @default.
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- W328304115 date "2007-01-01" @default.
- W328304115 modified "2023-09-23" @default.
- W328304115 title "Learning Random Monotone DNF." @default.
- W328304115 hasPublicationYear "2007" @default.
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