- Referenced in 47 articles
- smooth support vector machine for classification. Smoothing methods, extensively used for solving important mathematical programming ... pattern classification using a completely arbitrary kernel. We term such reformulation a Smooth Support Vector ... light [T. Joachims, in: Advances in kernel methods – support vector learning, MIT Press: Cambridge ... Platt, in: Advances in kernel methods – support vector learning, MIT Press: Cambridge, MA (1999)]. SSVM...
- Referenced in 57 articles
- Smola (eds.), Advances in kernel methods. London: MIT Press (1998; Zbl 0935.68084)] for classification problems...
- Referenced in 94 articles
- Library. This class of methods uses quite different computational kernels than the traditional simplex method...
- Referenced in 32 articles
- others. The np package focuses on kernel methods appropriate for the mix of continuous, discrete...
- Referenced in 19 articles
- page is devoted to learning methods building on kernels, such as the support vector machine ... here. In those days, information about kernel methods was sparse and nontrivial to find...
- Referenced in 21 articles
- Kernel Methods Matlab Toolbox. Key Features: SVM Classification using linear and quadratic penalization of misclassified ... Networks; SVM bounds (Span estimate, radius/margin); Wavelet Kernel; SVM Based Feature Selection; Kernel PCA; Kernel...
- Referenced in 37 articles
- Kernel-based Machine Learning Lab. Kernel-based machine learning methods for classification, regression, clustering, novelty ... reduction. Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes...
- Referenced in 44 articles
- contrast, previous analyses of stochastic gradient descent methods for SVMs require Ω(1/ϵ2) iterations ... linear kernel, the total run-time of our method is O (d/(λϵ)) , where ... approach also extends to non-linear kernels while working solely on the primal objective function ... magnitude speedup over previous SVM learning methods...
- Referenced in 15 articles
- many other recent developments in kernel based methods in general. Originally, it has been introduced ... theory and structural risk minimization. In the methods one solves convex optimization problems, typically quadratic ... exploit primal-dual interpretations. Links between kernel versions of classical pattern recognition algorithms such ... kernel PLS. Recent developments are in kernel spectral clustering, data visualization and dimensionality reduction...
- Referenced in 13 articles
- design of adaptive systems. It comprises methods for single- and multi-objective optimization (e.g., evolutionary ... gradient-based algorithms) as well as kernel-based methods, neural networks, and other machine learning...
- Referenced in 7 articles
- nonparametric measurement error problems using deconvolution kernel methods. We focus two measurement error models ... free data to the deconvolution kernel estimation. Several methods for the selection of the data...
- Referenced in 4 articles
- nonparametric density estimation. Operationally, the kernel method is used throughout to estimate the density. Diagnostics ... methods for evaluating the quality of the clustering are available. The package includes also ... probability density function obtained by the kernel method, given a set of data with arbitrary...
- Referenced in 38 articles
- Smoothing methods for nonparametric regression and density estimation. This is software linked to the book ... Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations’ Oxford University...
- Referenced in 55 articles
- spatial windows, pixel images and tessellations. Exploratory methods include K-functions, nearest neighbour distance ... space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross...
- Referenced in 40 articles
- modular software in which each statistical method (symbolic objects data base, distance matrix for symbolic ... objects, divisible classification of symbolic data, symbolic kernel discriminant analysis, symbolic description of groups, factorial ... like a chain with links the statistical methods. The top icon represents the symbolic data...
- Referenced in 3 articles
- library for high-dimensional kernel summations. Kernel-based methods are a powerful tool ... bottleneck in these methods is computations involving the kernel matrix, which scales quadratically with ... Kernel Independent Treecode), an efficient, scalable, kernel-independent method for approximately evaluating kernel matrix-vector ... novel, randomized method for efficiently factoring off-diagonal blocks of the kernel matrix using approximate...
- Referenced in 2 articles
- Performing the Kernel Method of Test Equating with the Package kequate. In standardized testing ... obtain a fair test. Recently, the kernel method of test equating, which is a conjoint ... test equating, has gained popularity. The kernel method of test equating includes five steps ... covariates. An R package for the kernel method of test equating called kequate is presented...
- Referenced in 6 articles
- traditional interleaving semantics. We show for terminating kernels that either both semantics compute identical results ... erroneously.par The result induces a method that allows GPU kernels with arbitrary reducible control flow ... that employs predicated execution. We implemented this method in the GPUVerify tool and experimentally evaluated ... Among these kernels, 42 exhibit unstructured control flow which our novel method can handle fully...
- Referenced in 244 articles
- robotics and motion planning, mesh generation, numerical methods... More on the projects using CGAL ... objects and predicates are regrouped in CGAL Kernels. Finally, the Support Library offers geometric object...
- Referenced in 22 articles
- Galerkin methods (finite and spectral element methods) in 1D, 2D And 3D to solve partial ... mathematical kernel solving easily problems using different techniques thus allowing testing and comparing methods...