Statistical and computational limits for sparse matrix detection
نویسندگان
چکیده
منابع مشابه
Statistical and Computational Limits for Sparse Matrix Detection
This paper investigates the fundamental limits for detecting a high-dimensional sparse matrix contaminated by white Gaussian noise from both the statistical and computational perspectives. We consider p×pmatrices whose rows and columns are individually k-sparse. We provide a tight characterization of the statistical and computational limits for sparse matrix detection, which precisely describe ...
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We consider one bit matrix completion under rank constraint. We present an estimator based on rank constrained maximum likelihood estimation, and an e cient greedy algorithm to solve it approximately based on an extension of conditional gradient descent. The output of the proposed algorithm converges at a linear rate to the underlying true low-rank matrix up to the optimal statistical estimatio...
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Kipadia, Nirav Harish. M.S.E.E., Purdue University. May 1994. Pi SIMD Sparse Matrix-Vector Multiplication Algorithm for Computational Electromagnetics and Scattering Matrix Models. Major Professor: Jose Fortes. A large number of problems in numerical analysis require the multiplication of a sparse matrix by a vector. In spite of the large amount of fine-grained parallelism available in the proc...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2020
ISSN: 0090-5364
DOI: 10.1214/19-aos1860