Who Cited It

The Nature of Statistical Learning Theory

1995 · 39,409 citations · 59 from inside this corpus

Vladimir Vapnik

No abstract in the source record.

The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Greedy function approximation: A gradient boosting machine. (2001)Greedy function approximation…Statistical Learning Theory (1999)Statistical Learning TheoryDeep learning in neural networks: An overview (2014)Deep learning in neural netwo…A Tutorial on Support Vector Machines for Pattern Recognition (1998)A Tutorial on Support Vector …Anomaly detection (2009)Anomaly detectionGaussian Processes for Machine Learning (2005)Gaussian Processes for Machin…Learning from Imbalanced Data (2009)Learning from Imbalanced DataLeast Squares Support Vector Machine Classifiers (1999)Least Squares Support Vector …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…The random subspace method for constructing decision forests (1998)The random subspace method fo…Pattern Recognition and Neural Networks (1996)Pattern Recognition and Neura…An overview of statistical learning theory (1999)An overview of statistical le…Estimating the Support of a High-Dimensional Distribution (2001)Estimating the Support of a H…Learning Deep Architectures for AI (2009)Learning Deep Architectures f…A Practical Guide to Support Vector Classication (2008)A Practical Guide to Support …Quantum machine learning (2017)Quantum machine learningStatistical Modeling: The Two Cultures (with comments and a rejoinder by the author) (2001)Statistical Modeling: The Two…Semi-Supervised Learning (2006)Semi-Supervised LearningSupervised Machine Learning: A Review of Classification Techniques (2007)Supervised Machine Learning: …Front-End Factor Analysis for Speaker Verification (2010)Front-End Factor Analysis for…Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review (2017)Deep Convolutional Neural Net…Support Vector Data Description (2003)Support Vector Data Descripti…An introduction to kernel-based learning algorithms (2001)An introduction to kernel-bas…A few useful things to know about machine learning (2012)A few useful things to know a…Sentiment analysis algorithms and applications: A survey (2014)Sentiment analysis algorithms…Understanding Machine Learning: From Theory To Algorithms (2015)Understanding Machine Learnin…A Short Introduction to Boosting (1999)A Short Introduction to Boost…Apprenticeship learning via inverse reinforcement learning (2004)Apprenticeship learning via i…Support Vector Machines for Classification and Regression (1998)Support Vector Machines for C…Support Vector Method for Function Approximation, Regression Estimation and Signal Proces… (1996)Support Vector Method for Fun…A re-examination of text categorization methods (1999)A gentle tutorial of the em algorithm and its application to parameter estimation for Gau… (1998)A gentle tutorial of the em a…Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…Logistic regression and artificial neural network classification models: a methodology re… (2002)Logistic regression and artif…Choosing Multiple Parameters for Support Vector Machines (2002)Choosing Multiple Parameters …
36 of 36 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 cites it, inside the corpus

PaperYearCited
Greedy function approximation: A gradient boosting machine.200130,137
Statistical Learning Theory199926,957
Deep learning in neural networks: An overview201418,236
A Tutorial on Support Vector Machines for Pattern Recognition199816,488
Anomaly detection200911,511
Gaussian Processes for Machine Learning200510,470
Learning from Imbalanced Data200910,209
Least Squares Support Vector Machine Classifiers19999,429
Nonlinear Component Analysis as a Kernel Eigenvalue Problem19988,138
Text categorization with Support Vector Machines: Learning with many relevant features19988,044
The random subspace method for constructing decision forests19986,904
Pattern Recognition and Neural Networks19966,514
An overview of statistical learning theory19996,311
Estimating the Support of a High-Dimensional Distribution20016,097
Learning Deep Architectures for AI20095,077
A Practical Guide to Support Vector Classication20085,074
Quantum machine learning20174,720
Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)20014,362
Semi-Supervised Learning20064,334
Supervised Machine Learning: A Review of Classification Techniques20074,149
Front-End Factor Analysis for Speaker Verification20103,605
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review20173,570
Support Vector Data Description20033,526
An introduction to kernel-based learning algorithms20013,498
A few useful things to know about machine learning20123,338
Sentiment analysis algorithms and applications: A survey20143,264
Understanding Machine Learning: From Theory To Algorithms20153,081
A Short Introduction to Boosting19992,952
Apprenticeship learning via inverse reinforcement learning20042,895
Support Vector Machines for Classification and Regression19982,831
Support Vector Method for Function Approximation, Regression Estimation and Signal Proces…19962,704
A re-examination of text categorization methods19992,664
A gentle tutorial of the em algorithm and its application to parameter estimation for Gau…19982,510
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
Logistic regression and artificial neural network classification models: a methodology re…20022,201
Choosing Multiple Parameters for Support Vector Machines20022,183

Links

DOI · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science

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complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports1 author record(s) attached.
  • supports2 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:40+00:00.

sha256 7e3d99a592f7f61f…