• 제목/요약/키워드: equivalent kernel

검색결과 30건 처리시간 0.019초

커널 이완절차에 의한 커널 공간의 저밀도 표현 학습 (Sparse Representation Learning of Kernel Space Using the Kernel Relaxation Procedure)

  • 류재홍;정종철
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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    • pp.60-64
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    • 2001
  • In this paper, a new learning methodology for Kernel Methods is suggested that results in a sparse representation of kernel space from the training patterns for classification problems. Among the traditional algorithms of linear discriminant function(perceptron, relaxation, LMS(least mean squared), pseudoinverse), this paper shows that the relaxation procedure can obtain the maximum margin separating hyperplane of linearly separable pattern classification problem as SVM(Support Vector Machine) classifier does. The original relaxation method gives only the necessary condition of SV patterns. We suggest the sufficient condition to identify the SV patterns in the learning epochs. Experiment results show the new methods have the higher or equivalent performance compared to the conventional approach.

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Nonparametric Discontinuity Point Estimation in Density or Density Derivatives

  • Huh, Jib
    • Journal of the Korean Statistical Society
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    • 제31권2호
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    • pp.261-276
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    • 2002
  • Probability density or its derivatives may have a discontinuity/change point at an unknown location. We propose a method of estimating the location and the jump size of the discontinuity point based on kernel type density or density derivatives estimators with one-sided equivalent kernels. The rates of convergence of the proposed estimators are derived, and the finite-sample performances of the methods are illustrated by simulated examples.

커널 이완 절차에 의한 커널 공간의 저밀도 표현 학습 (Spare Representation Learning of Kernel Space Using the Kernel Relaxation Procedure)

  • 류재홍;정종철
    • 한국지능시스템학회논문지
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    • 제11권9호
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    • pp.817-821
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    • 2001
  • 본 논문은 분류 문제의 훈련 패턴으로부터 형성되는 커널 공간의 저밀도 표현을 가능하게 하는 커널 방법에 대한 새로운 학습방법론을 제안한다. 선형 판별 함수에 대한 기존의 학습법 중에서 이완 절차가 SVM(Support Vector Machine) 분류기와 동등하게 선형분리 가능 패턴분류 문제의 최대 마진 분리 초평면을 얻을 수 있다. 기존의 이완 절차는 지원 백터에 대한 필요 조건을 만족한다. 본 논문에서는 학습 중 지원 벡터를 확인하기 위한 충분 조건을 제시한다. 순차적 학습을 위하여 기존의 SVM을 확장하고 커널 판별함수를 정의한 후에 체계적인 학습방법을 제시한다. 실험 결과는 새 방법이 기존의 방법과 동등하거나 우수한 분류 성능을 갖고있음을 보여준다.

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A NUMERICAL ALGORITHM FOR SINGULAR MULTI-POINT BVPS USING THE REPRODUCING KERNEL METHOD

  • Jia, Yuntao;Lin, Yingzhen
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제21권1호
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    • pp.51-60
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    • 2014
  • In this paper, we construct a complex reproducing kernel space for singular multi-point BVPs, and skillfully obtain reproducing kernel expressions. Then, we transform the problem into an equivalent operator equation, and give a numerical algorithm to provide the approximate solution. The uniform convergence of this algorithm is proved, and complexity analysis is done. Lastly, we show the validity and feasibility of the numerical algorithm by two numerical examples.

A FRAMEWORK TO UNDERSTAND THE ASYMPTOTIC PROPERTIES OF KRIGING AND SPLINES

  • Furrer Eva M.;Nychka Douglas W.
    • Journal of the Korean Statistical Society
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    • 제36권1호
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    • pp.57-76
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    • 2007
  • Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

ON THE TRANSFORMATION FORMULA OF THE SLICE BERGMAN KERNELS IN THE QUATERNION VARIABLES

  • Park, Jong-Do
    • 대한수학회보
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    • 제53권5호
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    • pp.1401-1409
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    • 2016
  • In complex analysis, the Bergman kernels for two biholomorphically equivalent complex domains satisfy the transformation formula. Recently new Bergman theory of slice regular functions of the quaternion variables has been investigated. In this paper we construct the transformation formula of the slice Bergman kernels under slice biregular functions in the setting of the quaternion variables.

On a Hilbert-Type Integral Inequality with a Combination Kernel and Applications

  • Yang, Bicheng
    • Kyungpook Mathematical Journal
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    • 제50권2호
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    • pp.281-288
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    • 2010
  • By introducing some parameters and using the way of weight function and the technic of real analysis and complex analysis, a new Hilbert-type integral inequality with a best constant factor and a combination kernel involving two mean values is given, which is an extension of Hilbert's integral inequality. As applications, the equivalent form and the reverse forms are considered.

CERTAIN FORM OF HILBERT-TYPE INEQUALITY USING NON-HOMOGENEOUS KERNEL OF HYPERBOLIC FUNCTIONS

  • Santosh Kaushik;Satish Kumar
    • Korean Journal of Mathematics
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    • 제31권2호
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    • pp.189-201
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    • 2023
  • In this article, we establish Hilbert-type integral inequalities with the help of a non-homogeneous kernel of hyperbolic function with best constant factor. We also study the obtained inequalities's equivalent form. Additionaly, several specific Hilbert's type inequalities with constant factors in the term of the rational fraction expansion of higher order derivatives of cotangent and cosine functions are presented.