• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.41-68
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• 2019

Multi-view learning considers data from various viewpoints as well as attempts to integrate various information from data. Multi-view learning has been studied recently and has showed superior performance to a model learned from only a single view. With the introduction of deep learning techniques to a multi-view learning approach, it has showed good results in various fields such as image, text, voice, and video. In this study, we introduce how multi-view learning methods solve various problems faced in human behavior recognition, medical areas, information retrieval and facial expression recognition. In addition, we review data integration principles of multi-view learning methods by classifying traditional multi-view learning methods into data integration, classifiers integration, and representation integration. Finally, we examine how CNN, RNN, RBM, Autoencoder, and GAN, which are commonly used among various deep learning methods, are applied to multi-view learning algorithms. We categorize CNN and RNN-based learning methods as supervised learning, and RBM, Autoencoder, and GAN-based learning methods as unsupervised learning.

• Journal of the Korean Magnetic Resonance Society
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• v.19 no.3
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• pp.124-131
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• 2015

Hyperpolarization methods are the most emerging techniques in the field of magnetic resonance (MR) researches since they make a contribution to overcoming sensitivity limitation of MR spectroscopy and imaging, leading to new fields of researches, real-time in vivo metabolic/molecular imaging and MR analysis of chemical/biological reactions in non-equilibrium conditions. Make use of enormous signal enrichments, it becomes feasible to investigate various chemical and biochemical systems with low ${\gamma}$ nuclei in real-time. This review deals with the theoretical principals of common hyperpolarization methods and their experimental features. In addition, more detailed theories, mechanisms, and applications of dissolution dynamic nuclear polarization (D-DNP) are discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.2
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• pp.55-64
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• 2005

In this paper, generalized difference methods(GDM) for one-dimensional viscoelastic problems are proposed and analyzed. The new initial values are given in the generalized difference scheme, so we obtain optimal error estimates in $L^p$ and $W^{1,p}(2\;{\leq}\;p\;{\leq}\;{\infty})$ as well as some superconvergence estimates in $W^{1,p}(2\;{\leq}\;p\;{\leq}\;{\infty})$ between the GDM solution and the generalized Ritz-Volterra projection of the exact solution.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.267-284
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• 2014

The multiresolution analysis for Legendre multiwavelets are given, anti-derivatives of Legendre multiwavelets are used for the numerical solution of differential equations, a special form of multilevel augmentation method algorithm is proposed to solve the disrete linear system efficiently, convergence rate of the Galerkin methods is given and numerical examples are presented.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.15 no.4
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• pp.267-275
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• 2011

This paper proposes a new quickly convergent pattern search quasi-Newton algorithm that employs the multi-step version of the Symmetric Rank One (SRI). The new algorithm works on the factorizations of the inverse Hessian approximations to make available a sequence of convergent positive bases required by the pattern search process. The algorithm, in principle, resembles that developed in [1] with multi-step methods dominating the dervation and with numerical improvements incurred, as shown by the numerical results presented herein.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.41-50
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• 2002

We provide local and semilocal theorems for the convergence of Newton-like methods to a locally unique solution of an equation in a Banach space. The analytic property of the operator involved replaces the usual domain condition for Newton-like methods. In the case of the local results we show that the radius of convergence can be enlarged. A numerical example is given to justify our claim . This observation is important and finds applications in steplength selection in predictor-corrector continuation procedures.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.477-485
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• 1997

Let E be a smooth Banach space. Suppose T:$E \rightarrow E$ is a strongly accretive map. It is proved that each of the two well known fixed point iteration methods (the Mann and ishikawa iteration methods), under suitable conditions converges strongly to a solution of the equation $T_x=f$.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1179-1191
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• 2011

In this paper, we introduce a new iterative scheme for finding a common element of the set of fixed points of a finite family of strict pseudocontractions and the solution set of pseudomonotone and Lipschitz-type continuous equilibrium problems. The scheme is based on the idea of extragradient methods and fixed point iteration methods. We show that the iterative sequences generated by this algorithm converge strongly to the common element in a real Hilbert space.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.25-35
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• 2009

In this paper, we study the regularity of induced splittings from multisplitting and two-stage multisplitting methods of monotone matrices under the assumption that splittings are weak regular, and we also study some comparison theorems for two-stage multisplitting methods of monotone matrices.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.621-634
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• 1999

Consider the several methods of constructing interval for relative ration from two independent binomial samples. The special interests are gives in the cases of low rates and small samples. bias-corrected and accelerated bootstrap method is proposed to overcome are the non-efficiency of current methods based on asymptotic resuts. Simulation studies are presented to demonstrate the performance of the proposed method.