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• W2139176861 abstract "The class of shuffle ideals is a fundamental sub-family of regular languages. The shuffle ideal generated by a string set U is the collection of all strings containing some string u ∈ U as a (not necessarily contiguous) subsequence. In spite of its apparent simplicity, the problem of learning a shuffle ideal from given data is known to be computationally intractable. In this paper, we study the PAC learn-ability of shuffle ideals and present positive results on this learning problem under element-wise independent and identical distributions and Markovian distributions in the statistical query model. A constrained generalization to learning shuffle ideals under product distributions is also provided. In the empirical direction, we propose a heuristic algorithm for learning shuffle ideals from given labeled strings under general unrestricted distributions. Experiments demonstrate the advantage for both efficiency and accuracy of our algorithm." @default.
• W2139176861 created "2016-06-24" @default.
• W2139176861 creator A5022904068 @default.
• W2139176861 date "2014-12-08" @default.
• W2139176861 modified "2023-09-24" @default.
• W2139176861 title "Learning Shuffle Ideals Under Restricted Distributions" @default.
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• W2139176861 hasPublicationYear "2014" @default.
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