Experiments performed on non-linearly-separable and real multi-labeled data sets show that proposed learning methods outperform the existing ones. 展开 关键词: Overlapping clustering Non-disjoint clusters Learning multi-labels Kernel methods Kernel K-means Nonlinear separations Non-linearly-separable ...
This paper presents the framework of kernel-based methods in the context of hyperspectral image classification, illustrating from a general viewpoint the main characteristics of different kernel-based approaches and analyzing their properties in the hyperspectral domain. In particular, we assess performance...
Kernel-based Methods and Function Approximation 2016 The guest editors of the mini-workshop Kernel-based Methods and Function Approximation discuss details and highlights of the meeting. R Cavoretto,AD Rossi - 《Dolomites Research Notes on Approximation》 被引量: 1发表: 2016年 On a Kernel-Based ...
- 《J Microbiol Methods》 被引量: 7发表: 2013年 A fractal-based 2D expansion method for multi-scale volume data visualization Visualization of volume data is difficult to realize and control because the most common output device is a two-dimensional (2D) display and the most commo... T ...
A class of kernel-based scalable algorithms for data science Indeed, the proposed algorithms are relevant for supervised or unsupervised learning, generative methods, and reinforcement learning.LeFloch, Philippe G... PG Lefloch,JM Mercier,S Miryusupov 被引量: 0发表: 2024年 加载更多来源...
In this paper, we presented a connection between boosting and kernel-based methods. We showed that in the context of regularized least-squares, boosting with a weak learner is equivalent to using a boosting kernel. This connection also implies that learning rates and consistency analysis on kernel...
Kernel-based methods for inversion of the Radon transform on SO(3) and their applications to texture analysis 来自 国家科技图书文献中心 喜欢 0 阅读量: 35 作者:KGVD Boogaart,R Hielscher,J Prestin,H Schaeben 摘要: Texture analysis is used here as short term for analysis of crystallographic ...
Input Space Versus Feature Space in Kernel-Based Methods. Presents information on a study which discussed some ways to understand feature spaces associated with support vector kernel functions. Discussion on geome... Scholkopf,Bernhard,Mika,... - 《IEEE Transactions on Neural Networks》 被引量: ...
Further, using a urinary metabolomics data set (from a toxicity study) and principal component analysis (PCA), we showed that the information content in the quantified features was equivalent for Gaussian and uniform binning methods. The separation between groups in the PCA scores plot, measured ...
In the computation process of many kernel methods, one of the important step is the formation of the kernel matrix. But the size of kernel matrix scales with the number of data set, it is infeasible to store and compute the kernel matrix when faced with the large-scale data set. To over...