نتایج جستجو برای: introverted subspace

تعداد نتایج: 18107  

Journal: :Comprehensive psychiatry 2003
Nancy L Talbot Paul R Duberstein Jessica S Butzel Christopher Cox Donna E Giles

The influence of personality on symptom reduction has not been examined in research on treatments for women with childhood sexual abuse histories, although personality has demonstrated predictive value in other treatment contexts. This study examined personality variables associated with symptom reduction in group therapy for hospitalized women with histories of sexual abuse. Personality was me...

2016
Mitch Brown Donald F. Sacco

Human facial structures communicate health, thus indicating one's suitability as a potential mating partner. However, facial structures also communicate information about one's personality, which allows for inferences about a target's behavioral intentions. A target's relative level of extraversion can be reliably inferred from facial structural features. Because past research has found an asso...

Journal: :bulletin of the iranian mathematical society 2014
amer kaabi

‎the global fom and gmres algorithms are among the effective‎ ‎methods to solve sylvester matrix equations‎. ‎in this paper‎, ‎we‎ ‎study these algorithms in the case that the coefficient matrices‎ ‎are real symmetric (real symmetric positive definite) and extract‎ ‎two cg-type algorithms for solving generalized sylvester matrix‎ ‎equations‎. ‎the proposed methods are iterative projection metho...

Journal: :Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2001

Journal: :Journal of Mathematical Analysis and Applications 2011

Journal: :Ricerche di Matematica 2020

Journal: :IEEE Transactions on Signal Processing 2001

Journal: :IEEE Transactions on Signal Processing 1994

Journal: :IEEE Transactions on Knowledge and Data Engineering 2021

Subspace clustering assumes that the data is separable into separate subspaces. Such a simple assumption, does not always hold. We assume that, even if raw subspaces, one can learn representation (transform coefficients) such learnt To achieve intended goal, we embed subspace techniques (locally linear manifold clustering, sparse and low rank representation) transform learning. The entire formu...

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