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Statistical Inference of Minimum Rank Factor Analysis
Psychometrika, 2002For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the unexplained common variance with that number of factors is minimized, subject to the constraint that both the diagonal matrix of unique variances and the observed covariance matrix minus that diagonal matrix
Shapiro, A, Ten Berge, JMF
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Minimum Rank Error Language Modeling
IEEE Transactions on Audio, Speech, and Language Processing, 2009Statistical language modeling has been successfully developed for speech recognition and information retrieval. The minimum classification error (MCE) training was undertaken to enhance speech recognition performance by minimizing the word error rate.
null Jen-Tzung Chien, null Meng-Sung Wu
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2018
Haemers’ minimum rank, η(G), was first defined by Willem Haemers in 1979. He created this graph parameter as an upper bound for the Shannon capacity of a graph, Θ(G), and to answer some questions asked by Lovasz in his famous paper where he determined Θ(C5) = √ 5.
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Haemers’ minimum rank, η(G), was first defined by Willem Haemers in 1979. He created this graph parameter as an upper bound for the Shannon capacity of a graph, Θ(G), and to answer some questions asked by Lovasz in his famous paper where he determined Θ(C5) = √ 5.
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Maximal rank minimum aberration and doubling
Statistics & Probability Letters, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Jianwei, Zhang, Runchu
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On the Minimum Violations Ranking of a Tournament
Management Science, 1986This paper examines the problem of rank ordering a set of players or objects on the basis of a set of pairwise comparisons arising from a tournament. The criterion for deriving this ranking is to have as few cases as possible where player i is ranked above j while i was actually defeated by j in the tournament.
Iqbal Ali, Wade D. Cook, Moshe Kress
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Minimum-volume Rank-deficient Nonnegative Matrix Factorizations
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019In recent years, nonnegative matrix factorization (NMF) with volume regularization has been shown to be a powerful identifiable model; for example for hyperspectral unmixing, document classification, community detection and hidden Markov models. In this paper, we show that minimum-volume NMF (min-vol NMF) can also be used when the basis matrix is rank ...
Leplat, Valentin +2 more
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On graphs of minimum skew rank 4
Linear and Multilinear Algebra, 2015The zero–nonzero pattern of a skew-symmetric matrix defines a graph. The minimum rank of all real skew-symmetric matrices with a given graph is studied. The probabilistic method is used to show that for sufficiently large , there is a regular graph of order whose complement has girth at least 5 and for which every skew-symmetric matrix with graph has ...
Sudipta Mallik, Bryan L. Shader
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The minimum rank over a field F of a graph G is the smallest possible rank among all symmetric matrices over F whose ( i , j )th entry ( i ≠ j ) is nonzero whenever ij is an edge in G and is zero otherwise, where zero is the additive identity of F. A universally optimal matrix for a graph G is an integer symmetric matrix A such that every off-diagonal ...
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The Minimum Acceptable Violation Ranking of Alternatives from Voters’ Ordinal Rankings
2015Motived by applications of ordinal ranking and adjustment consensus in group decision making, we study the problem of aggregating all voters' ordinal ranking on a set of alternatives into an adjusted "consensus" ranking. In this problem, every voter ranks a set of alternatives respectively, and we know the adjustment acceptability.
Kelin Luo, Yinfeng Xu
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Linear and Multilinear Algebra, 2005
Let Sn (F) be the set of all n × n symmetric matrices over a field F. For a matrix denotes the rank of A. A pair of n × n matrices ( A, B ) is said to be rank-sum-maximal if , rank-sum-minimal if and rank-subtractive if . We say that a linear operator ϕ from Sn (F) to itself is a linear preserver of rank-sum-maximum (respectively, rank-sum-minimum and ...
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Let Sn (F) be the set of all n × n symmetric matrices over a field F. For a matrix denotes the rank of A. A pair of n × n matrices ( A, B ) is said to be rank-sum-maximal if , rank-sum-minimal if and rank-subtractive if . We say that a linear operator ϕ from Sn (F) to itself is a linear preserver of rank-sum-maximum (respectively, rank-sum-minimum and ...
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