Skip to search formSkip to main contentSkip to account menu

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… 
Wikipedia (opens in a new tab)

Related topics

Related topics

35 relations
3D reconstructionAdaptive filterArtificial neural networkBioinformatics

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
Construction of semantic bootstrapping models for relation extraction
2013
2013
Fault Detection of Non-Gaussian Processes Based on Model Migration
In this paper, a new modeling approach is proposed for common and specific feature extraction. The original space of a mode can… 
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… 
2011
2011
Wavelet kernel learning
2009
2009
Efficient multi-label classification with hypergraph regularization
Many computer vision applications, such as image classification and video indexing, are usually multi-label classification… 
Review
2007
Review
2007
Kernel Fisher discriminant functions – a concise and rigorous introduction
In the article the application of kernel functions – the so-called »kernel trick« – in the context of Fisher’s approach to linear… 
2006
2006
Reasoning by Analogy in Description Logics Through Instance-based Learning
This work presents a method founded in instancebased learning for inductive (memory-based) reasoning on ABoxes. The method, which… 
Highly Cited
2004
Highly Cited
2004
Communication In General Decentralised Filters And The Coordinated Search Strategy
This paper addresses the problem of coordinating multiple heterogeneous sensing platforms performing a search mission for a… 
2002
2002
Forward Decoding Kernel Machines: A Hybrid HMM/SVM Approach to Sequence Recognition
Forward Decoding Kernel Machines (FDKM) combine largemargin classifiers with Hidden Markov Models (HMM) for Maximum a Posteriori… 
1987
1987
The Abstraction/Implementation Model of Problem Reformulation
A good problem representation incorporates important problem constraints while hiding superfluous detail. This paper presents… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)