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Kernel method

Known as: Kernel Methods, KM, Kernel machines 
In machine learning, kernel methods are a class of algorithms for pattern analysis, whose best known member is the support vector machine (SVM). The… 
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Related topics

Related topics

35 relations
3D reconstructionAdaptive filterArtificial neural networkBioinformatics

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2016
Highly Cited
2016
Kernelized Multiview Projection for Robust Action Recognition
Conventional action recognition algorithms adopt a single type of feature or a simple concatenation of multiple features. In this… 
Highly Cited
2012
Highly Cited
2012
A Novel Algorithm for Finding Reducts With Fuzzy Rough Sets
Attribute reduction is one of the most meaningful research topics in the existing fuzzy rough sets, and the approach of… 
Highly Cited
2012
Highly Cited
2012
Fourier Kernel Learning
Approximations based on random Fourier embeddings have recently emerged as an efficient and formally consistent methodology to… 
Highly Cited
2009
Highly Cited
2009
Kernel Grassmannian distances and discriminant analysis for face recognition from image sets
Highly Cited
2008
Highly Cited
2008
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick… 
Highly Cited
2006
Highly Cited
2006
Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis
High-dimensional data appear in many applications of data mining, machine learning, and bioinformatics. Feature reduction is… 
Highly Cited
2003
Highly Cited
2003
On the Use of Kernel PCA for Feature Extraction in Speech Recognition
This paper describes an approachfor feature extraction in speech recognition systems using kernel principal componentanalysis… 
Review
2003
Review
2003
Reconstruction of Patterns from Noisy Inputs Using Morphological Associative Memories
Morphological neural networks are based on a new paradigm for neural computing. Instead of adding the products of neural values… 
Review
2001
Review
2001
An introduction to support vector machines for data mining
With increasing amounts of data being generated by businesses and researchers there is a need for fast, accurate and robust… 
Highly Cited
2001
Highly Cited
2001
Face Recognition Using Kernel Methods
Principal Component Analysis and Fisher Linear Discriminant methods have demonstrated their success in face detection… 
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