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On learning Read-k-Satisfy-j DNF

机译:关于学习Read-k-Satisfy-j DNF

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摘要

We study the learnability of Read-k-Satisfy-j (RkSj) DNF formulae. These are DNF formulae in which the maximal number of occurrences of a variable is bounded by k, and the number of terms satisfied by any assignment is at most j. We show that this class of functions is learnable in polynomial time, using Equivalence and Membership Queries, as long as k•j=O(logn/loglogn). Learnability was previously known only in case that both k and j are constants. We also present a family of boolean functions that have short (poly(n)) Read-2-Satisfy-1 DNF formulae but require CNF formulae of size 2Wn . Therefore, our result does not seem to follow from the recent learnability result of [Bsh93].

机译:

我们研究了Read- k -Satisfy- j (RkSj)DNF公式的可学习性。这些是DNF公式,其中变量的最大出现次数由 k 限制,并且任何赋值满足的项数最多为 j 。我们证明只要 k•j = O (log n / loglog n )。以前仅在 k j 是常量的情况下才知道可学习性。我们还介绍了一个布尔函数家族,它们具有短的( poly(n))Read-2-Satisfy-1 DNF公式,但需要大小> 2 <的CNF公式。 SUP> W n 。因此,我们的结果似乎与[Bsh93]的最新可学习性结果不一致。

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