YIHONG WU THESIS

Computational barriers in minimax submatrix detection. Article information Source Ann. MR Digital Object Identifier: More like this Computational and statistical boundaries for submatrix localization in a large noisy matrix Cai, T. You have access to this content. You have partial access to this content. References [1] Addario-Berry, L.

Permanent link to this document https: Download Email Please enter a valid email address. You have access to this content. Implications on the hardness of support recovery are also obtained. More by Zongming Ma Search this author in: On combinatorial testing problems. Using Schatten norm loss as a representative example, we show that the hardness of attaining the minimax estimation rate can crucially depend on the loss function.

yihong wu thesis

References [1] Addario-Berry, L. Minimax procedures Keywords Asymptotic equivalence high-dimensional statistics computational complexity minimax rate planted clique submatrix detection Citation Ma, Zongming; Wu, Yihong. You have partial access to this content. You have access to this content. Ma, Zongming; Wu, Yihong.

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Under the hypothesis that the planted clique detection problem cannot be solved in randomized polynomial time when the clique size is of smaller order than the square root of the graph size, the following phase transition phenomenon is established: More by Zongming Thesks Search this author theiss You do not have access to this content. Permanent link to this document https: More by Yihong Wu Search this author in: We provide proofs of Theorem 1 and Lemmas 5 and 6.

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December First available in Project Euclid: Download Email Please enter a valid email address. Keywords Asymptotic equivalence high-dimensional statistics computational complexity minimax rate planted clique submatrix detection.

To investigate the tradeoff between statistical performance and computational cost from a complexity-theoretic perspective, we consider a sequence of discretized models which are asymptotically equivalent to the Gaussian model. Computational and statistical boundaries for submatrix localization in a large noisy matrix Cai, T. Using Schatten norm loss as a representative example, we show that the hardness of attaining the minimax estimation rate can crucially depend on the loss function.

yihong wu thesis

Computational barriers in minimax submatrix detection. Article information Source Ann.

Implications on the hardness of support recovery are also obtained. Zentralblatt MATH identifier Abstract Article info and citation First page References Supplemental materials Abstract This paper studies the minimax detection of a small submatrix of elevated mean in a large matrix contaminated by additive Gaussian noise.

Ma , Wu : Computational barriers in minimax submatrix detection

Tuesis Digital Object Identifier: Google Scholar Project Euclid. More like this Computational and statistical boundaries for submatrix localization in a large noisy matrix Cai, T. This paper studies the minimax detection of a small submatrix of elevated mean in a large matrix contaminated by additive Gaussian noise.

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On combinatorial testing problems.