Who Cited It

An introduction to kernel-based learning algorithms

2001 · IEEE Transactions on Neural Networks · 3,498 citations · 11 from inside this corpus

K. Müller low, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

An introduction to kernel-based learning algorithms (2001)An introduction to kernel-bas…Support-vector networks (1995)Support-vector networksThe Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Support-Vector Networks (1995)Support-Vector NetworksNeural Networks: A Comprehensive Foundation (1998)Neural Networks: A Comprehens…Statistical Learning Theory (1999)Statistical Learning TheoryNeural networks for pattern recognition (1994)Neural networks for pattern r…A Tutorial on Support Vector Machines for Pattern Recognition (1998)A Tutorial on Support Vector …Neural Networks for Pattern Recognition (1995)Neural Networks for Pattern R…A training algorithm for optimal margin classifiers (1992)A training algorithm for opti…Introduction to Statistical Pattern Recognition (1990)Introduction to Statistical P…Learning with Kernels (2001)Learning with KernelsSolutions of Ill-Posed Problems. (1978)Solutions of Ill-Posed Proble…Nonlinear Component Analysis as a Kernel Eigenvalue Problem (1998)Nonlinear Component Analysis …Text categorization with Support Vector Machines: Learning with many relevant features (1998)Text categorization with Supp…Neural networks: A comprehensive foundation (1995)Neural networks: A comprehens…Estimating the Support of a High-Dimensional Distribution (2001)Estimating the Support of a H…Advances in kernel methods: support vector learning (1999)Advances in kernel methods: s…Making Large-Scale SVM Learning Practical (2006)Making Large-Scale SVM Learni…Fast Learning in Networks of Locally-Tuned Processing Units (1989)Fast Learning in Networks of …An Introduction to Support Vector Machines (2000)An Introduction to Support Ve…Introduction to statistical pattern recognition (2nd ed.) (1990)Introduction to statistical p…Neural Networks and the Bias/Variance Dilemma (1992)Neural Networks and the Bias/…The Strength of Weak Learnability (1990)The Strength of Weak Learnabi…An Introduction to the Bootstrap. (1994)An Introduction to the Bootst…Learning with Kernels (2001)Learning with KernelsSurvey of Clustering Algorithms (2005)Survey of Clustering Algorith…Estimating the Support of a High-Dimensional Distribution (2001)Estimating the Support of a H…Distance Metric Learning for Large Margin Nearest Neighbor Classification (2009)Distance Metric Learning for …Quantum Support Vector Machine for Big Data Classification (2014)Quantum Support Vector Machin…A Comprehensive Survey of Clustering Algorithms (2015)A Comprehensive Survey of Clu…Improvements to Platt's SMO Algorithm for SVM Classifier Design (2001)Improvements to Platt's SMO A…Distance Metric Learning for Large Margin Nearest Neighbor Classification (2005)Distance Metric Learning for …Generalized Discriminant Analysis Using a Kernel Approach (2000)Generalized Discriminant Anal…An overview of text-independent speaker recognition: From features to supervectors (2009)An overview of text-independe…Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications (2021)Explaining Deep Neural Networ…Explaining nonlinear classification decisions with deep Taylor decomposition (2016)
36 of 46 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Support-vector networks199541,028
The Nature of Statistical Learning Theory199539,409
Support-Vector Networks199533,914
Neural Networks: A Comprehensive Foundation199829,840
Statistical Learning Theory199926,957
Neural networks for pattern recognition199418,720
A Tutorial on Support Vector Machines for Pattern Recognition199816,488
Neural Networks for Pattern Recognition199512,273
A training algorithm for optimal margin classifiers199211,664
Introduction to Statistical Pattern Recognition199011,140
Learning with Kernels20019,631
Solutions of Ill-Posed Problems.19788,221
Nonlinear Component Analysis as a Kernel Eigenvalue Problem19988,138
Text categorization with Support Vector Machines: Learning with many relevant features19988,044
Neural networks: A comprehensive foundation19957,270
Estimating the Support of a High-Dimensional Distribution20016,097
Advances in kernel methods: support vector learning19995,819
Making Large-Scale SVM Learning Practical20064,326
Fast Learning in Networks of Locally-Tuned Processing Units19894,230
An Introduction to Support Vector Machines20004,134
Introduction to statistical pattern recognition (2nd ed.)19903,814
Neural Networks and the Bias/Variance Dilemma19923,612
The Strength of Weak Learnability19903,344
An Introduction to the Bootstrap.19943,241
Learning with Kernels20012,541

What cites it, inside the corpus

PaperYearCited
Survey of Clustering Algorithms20056,210
Estimating the Support of a High-Dimensional Distribution20016,097
Distance Metric Learning for Large Margin Nearest Neighbor Classification20094,256
Quantum Support Vector Machine for Big Data Classification20142,010
A Comprehensive Survey of Clustering Algorithms20151,939
Improvements to Platt's SMO Algorithm for SVM Classifier Design20011,819
Distance Metric Learning for Large Margin Nearest Neighbor Classification20051,707
Generalized Discriminant Analysis Using a Kernel Approach20001,683
An overview of text-independent speaker recognition: From features to supervectors20091,453
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications20211,424
Explaining nonlinear classification decisions with deep Taylor decomposition20161,413

Links

DOI · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Face and Expression RecognitionComputer Science
Machine Learning and Data ClassificationComputer Science

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complete

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  • supports4 author record(s) attached.
  • supports210 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

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