Mutual Information Matrices Are Not Always Positive Semidefinite
نویسندگان
چکیده
منابع مشابه
Singular value inequalities for positive semidefinite matrices
In this note, we obtain some singular values inequalities for positive semidefinite matrices by using block matrix technique. Our results are similar to some inequalities shown by Bhatia and Kittaneh in [Linear Algebra Appl. 308 (2000) 203-211] and [Linear Algebra Appl. 428 (2008) 2177-2191].
متن کاملsingular value inequalities for positive semidefinite matrices
in this note, we obtain some singular values inequalities for positive semidefinite matrices by using block matrix technique. our results are similar to some inequalities shown by bhatia and kittaneh in [linear algebra appl. 308 (2000) 203-211] and [linear algebra appl. 428 (2008) 2177-2191].
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We build upon the work of Fukuda et al. [SIAM J. Optim., 11 (2001), pp. 647–674] and Nakata et al. [Math. Program., 95 (2003), pp. 303–327], in which the theory of partial positive semidefinite matrices was applied to the semidefinite programming (SDP) problem as a technique for exploiting sparsity in the data. In contrast to their work, which improved an existing algorithm based on a standard ...
متن کاملSingular Value Inequalities for Positive Semidefinite Matrices
In this note, we obtain some singular values inequalities for positive semidefinite matrices by using block matrix technique. Our results are similar to some inequalities shown by Bhatia and Kittaneh in [Linear Algebra Appl. 308 (2000) 203-211] and [Linear Algebra Appl. 428 (2008) 2177-2191].
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In this project, we are interested in approximating permanents of positive semidefinite Hermitian matrices. Specifically, we find conditions on positive semidefinite Hermitian matrices such that we can generalize the algorithm described in Sections 3.6 3.7 of [1] to matrices satisfying these conditions.
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2014
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2014.2311434