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On the Fourier spectrum of monotone functions

Authors:

Nader H. Bshouty,

Christino TamonAuthors Info & Claims

STOC '95: Proceedings of the twenty-seventh annual ACM symposium on Theory of computing

Pages 219 - 228

https://doi.org/10.1145/225058.225125

Published: 29 May 1995 Publication History

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Cited By

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Rubinfeld RVasilyan ASaha BServedio R(2023)Testing Distributional Assumptions of Learning AlgorithmsProceedings of the 55th Annual ACM Symposium on Theory of Computing10.1145/3564246.3585117(1643-1656)Online publication date: 2-Jun-2023
https://dl.acm.org/doi/10.1145/3564246.3585117
Drake AVentura D(2014)Improving Spectral Learning by Using Multiple RepresentationsProceedings of the 2014 13th International Conference on Machine Learning and Applications10.1109/ICMLA.2014.28(147-152)Online publication date: 3-Dec-2014
https://dl.acm.org/doi/10.1109/ICMLA.2014.28
Sitharam MStraney T(2005)Derandomized learning of boolean functionsAlgorithmic Learning Theory10.1007/3-540-63577-7_38(100-115)Online publication date: 9-Jun-2005
https://doi.org/10.1007/3-540-63577-7_38

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On the Fourier spectrum of monotone functions

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On the Fourier spectrum of monotone functions
Fourier transforms and bent functions on finite groups

Let G be a finite nonabelian group. Bent functions on G are defined by the Fourier transforms at irreducible representations of G. We introduce a dual basis $${\widehat{G}}$$G^, consisting of functions on G determined by its unitary irreducible ...
On the Fourier spectrum of symmetric Boolean functions

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What is the smallest t such that every symmetric boolean function on κ variables (which is not a constant or a parity function), has a non-zero Fourier coefficient of order at least 1 and at most t?

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STOC '95: Proceedings of the twenty-seventh annual ACM symposium on Theory of computing

May 1995

776 pages

ISBN:0897917189

DOI:10.1145/225058

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 May 1995

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STOC95: Symposium on Theory of Computing

May 29 - June 1, 1995

Nevada, Las Vegas, USA

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Cited By

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Rubinfeld RVasilyan ASaha BServedio R(2023)Testing Distributional Assumptions of Learning AlgorithmsProceedings of the 55th Annual ACM Symposium on Theory of Computing10.1145/3564246.3585117(1643-1656)Online publication date: 2-Jun-2023
https://dl.acm.org/doi/10.1145/3564246.3585117
Drake AVentura D(2014)Improving Spectral Learning by Using Multiple RepresentationsProceedings of the 2014 13th International Conference on Machine Learning and Applications10.1109/ICMLA.2014.28(147-152)Online publication date: 3-Dec-2014
https://dl.acm.org/doi/10.1109/ICMLA.2014.28
Sitharam MStraney T(2005)Derandomized learning of boolean functionsAlgorithmic Learning Theory10.1007/3-540-63577-7_38(100-115)Online publication date: 9-Jun-2005
https://doi.org/10.1007/3-540-63577-7_38

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