Predicting visual aesthetic preferences in Tehran city universities campuses using machine learning techniques. [PDF]
Sci RepSalehi Kousalari F +4 more
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Single replica spin-glass phase detection using field variation and machine learning. [PDF]
PLoS OneTalebi A +3 more
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Enhancing forensic clinical competence through scenario-based simulation: A comparative study of educational outcomes in Chinese medical students. [PDF]
PLoS OneLi J +6 more
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Probing Surface Degradation Pathways of Charged Nickel-Oxide Cathode Materials Using Machine-Learning Interatomic Potentials. [PDF]
ACS Appl Mater InterfacesBoth S +4 more
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Longitudinal relationships among early adolescent physical exercise, internalizing symptoms, and learning engagement: exploring within-person dynamics and the role of gender differences. [PDF]
Child Adolesc Psychiatry Ment HealthWei B +6 more
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Bidirectional and longitudinal associations among teacher-student relationships, peer relationships, and learning engagement in Chinese primary school students: a cross-lagged panel model. [PDF]
Front PsycholZhang J, Liu C.
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A NOTE ON STABILITY OF ERROR BOUNDS IN STATISTICAL LEARNING THEORY
Analysis and Applications, 2011 We consider a wide class of error bounds developed in the context of statistical learning theory which are expressed in terms of functionals of the regression function, for instance, its norm in a reproducing kernel Hilbert space or other functional space.
Ming Li, Andrea Caponnetto
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Stability Certificates for Neural Network Learning-based Controllers using Robust Control Theory
2021 American Control Conference (ACC), 2021 Providing stability guarantees for controllers that use neural networks can be challenging. Robust control theoretic tools are used to derive a framework for providing nominal stability guarantees – stability guarantees for a known nominal system – controlled by a learning-based neural network controller.
Nguyen Hoang Hai +5 more
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Stability theory of universal learning network
1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929), 2002 Higher order derivatives of the universal learning network (ULN) has been previously derived by forward and backward propagation computing methods, which can model and control the large scale complicated systems such as industrial plants, economic, social and life phenomena. In this paper, a new concept of nth order asymptotic orbital stability for the
Kotaro Hirasawa +3 more
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