Incoherent success
نویسندگان
چکیده
منابع مشابه
Learning Incoherent Subspaces: Classification via Incoherent Dictionary Learning
In this article we present the supervised iterative projections and rotations (s-ipr) algorithm, a method for learning discriminative incoherent subspaces from data. We derive s-ipr as a supervised extension of our previously proposed iterative projections and rotations (ipr) algorithm for incoherent dictionary learning, and we employ it to learn incoherent sub-spaces that model signals belongi...
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Proposition 1. (Grunewald [5, Proposition B]) Let F be a free group of rank k ≥ 2, generated by {s1, . . . , sk}. Let r1, . . . , rm be words over {s1, . . . , sk} ±1 and R their normal closure 〈〈r1, . . . , rm〉〉F in F . Let H be the group with presentation 〈s1, . . . , sk | r1, . . . , rm〉 and φ the canonical epimorphism φ : F → H ∼= F/R. Let F be a free group of rank k generated by {t1, . . ....
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ژورنال
عنوان ژورنال: Nature Photonics
سال: 2017
ISSN: 1749-4885,1749-4893
DOI: 10.1038/s41566-017-0080-5