kernel method
An Adaptive Non-parametric Kernel Method for Classification
... statistical method of estimating an underlying distribution from a set of samples is the non–parametric kernel ...This method can be used in classification to estimate the underlying distributions of ...
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A modified kernel method for a time fractional inverse diffusion problem
... In this paper, we consider a time-fractional inverse diffusion problem, where the data is given at x = 1 and the solution is sought in the interval 0 ≤ x < 1. Such a problem is obtained from the classical diffusion ...
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A Modified Degenerate Kernel Method for the System of Fredholm Integral Equations of the Second Kind
... Abstract. In this paper, the system of Fredholm integral equations of the second kind is investigated by using a modified degenerate kernel method (MDKM). To construct a MDKM the source function is approxi- ...
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Kernel Method for Persistence Diagrams via Kernel Embedding and Weight Factor
... a kernel method for persistence diagrams to develop a statistical framework in ...proposed kernel is stable under perturbation of data, enables one to explicitly control the effect of persistence by ...
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A new kernel method for hyperspectral image feature extraction
... (OMNF) method. This method adopts spectral and spatial decorrelation (SSDC) method to estimate noise by considering the high corre- lation between ...
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Effect of PET-MR Inconsistency in the Kernel Image Reconstruction Method
... hybrid kernel method to perform direct Patlak reconstruction from dynamic PET using MR and PET information where the latter was obtained by combining different ...a method using a spatially ...
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UnibucKernel: A kernel based learning method for complex word identification
... In this paper, we present a kernel-based learn- ing approach for the 2018 Complex Word Identification (CWI) Shared Task. Our ap- proach is based on combining multiple low- level features, such as character ...
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Title: A Novel Kernel Based Fuzzy C Means Clustering With Cluster Validity Measures
... Gaussian-function-based kernel fuzzy clustering is corrected, and a kernel fuzzy c-means clustering-based fuzzy SVM algorithm (KFCM-FSVM) is developed by [14] to deal with the classification problems with ...
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A Kernel PCA Method for Superior Word Sense Disambiguation
... new method for disambiguating word senses that exploits a nonlinear Kernel Prin- cipal Component Analysis (KPCA) technique to achieve accuracy superior to the best published indi- vidual ...of kernel ...
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Kernel Estimation in Line Transect Sampling for Parametric Model
... common method used in ecology for sampling the sample ...present kernel method to propose new estimator of the propose population ...density. Kernel estimation method is used due to ...
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Multiple kernels learning-based biological entity relationship extraction method
... graph kernel method [43] is one of the most typ- ical methods in the protein relationship extraction ...graph kernel method and all-paths graph kernel method in terms of their ...
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Learning a Robust Relevance Model for Search Using Kernel Methods
... semi-definite kernel under certain ...semi-definite kernel function called S-kernel and learn a robust relevance model using a kernel method based on ...a kernel method ...
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A Refined MCMC Sampling from RKHS for PAC-Bayes Bound Calculation
... Reproducing Kernel Hilbert Space (RKHS) using the kernel method, we proposed a refined Markov Chain Monte Carlo (MCMC) sampling algorithm by incorporating feedback information of the simulated model ...
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A Sampling Method Based on Gauss Kernel Learning and the Expanding Research
... on kernel learning to solve classification on imbalance dataset by Support Vector Machine ...The method first preprocesses the data by oversampling the minority class in kernel space, and then the ...
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Numerical Method for solving Volterra Integral Equations with a Convolution Kernel
... numerical method for solv- ing the Volterra integral equation with a convolution ...The method is described and illustrated with numerical ...the method is accurate and easy to ...
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Object Tracking using HOG and SVM
... Abstract — Object detection and tracking is a vital task among computer vision researchers. The main objective of object detection and tracking is to establish correspondence of objects and object parts between ...
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Single Corn Kernel Aflatoxin B1 Extraction and Analysis Method
... Table 2 demonstrates the average percent recoveries and relative standard deviation (RSD) values obtained from the spiked corn samples after performing the single maize kernel aflatoxin extraction. The analysis ...
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An Analog Circuit Diagnosis Method Based on Adaptive-Kernel ICA
... the method of the minimum detectable fault size ...MDFS method according to the specific circuit, we suppose the circuit occurs to soft fault that the values of the circuit components deviate 10% from the ...
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Title: Kernel Based Tagging Method Using Spatial Paradigm
... Abstract: The aptitude to select those standings from a given assembly that are most telltale of geographic location is of key reputation in efficaciously addressing this task.This procedure of selecting spatially ...
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Using String Kernels to Identify Performers from their Playing Style
... string kernel on this data, both kernel partial least squares and Sup- port Vector Machines outperform the current best ...new method of obtaining feature directions from the Ker- nel Partial Least ...
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