Who Cited It

Support-Vector Networks

1995 · Machine Learning · 33,914 citations · 36 from inside this corpus

Corinna Cortes, Vladimir Vapnik

No abstract in the source record.

Support-Vector Networks (1995)Support-Vector NetworksLearning representations by back-propagating errors (1986)Learning representations by b…A training algorithm for optimal margin classifiers (1992)A training algorithm for opti…Learning Internal Representations by Error Propagation (1988)Learning Internal Representat…A Tutorial on Support Vector Machines for Pattern Recognition (1998)A Tutorial on 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…Pattern Recognition and Neural Networks (1996)Pattern Recognition and Neura…An overview of statistical learning theory (1999)An overview of statistical le…Large-Scale Machine Learning with Stochastic Gradient Descent (2010)Large-Scale Machine Learning …Extreme Learning Machine for Regression and Multiclass Classification (2011)Extreme Learning Machine for …Learning Deep Architectures for AI (2009)Learning Deep Architectures f…A Practical Guide to Support Vector Classication (2008)A Practical Guide to Support …Active Learning Literature Survey (2009)Active Learning Literature Su…Semi-Supervised Learning (2006)Semi-Supervised LearningAn introduction to kernel-based learning algorithms (2001)An introduction to kernel-bas…Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases … (2017)Diagnostic Assessment of Deep…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…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…Support Vector Machines for Classification and Regression (1998)Support Vector Machines for C…A re-examination of text categorization methods (1999)A re-examination of text cate…Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…Choosing Multiple Parameters for Support Vector Machines (2002)Choosing Multiple Parameters …The Boosting Approach to Machine Learning: An Overview (2003)The Boosting Approach to Mach…Kernel principal component analysis (1997)Kernel principal component an…Stochastic Gradient Descent Tricks (2012)Stochastic Gradient Descent T…Extreme learning machines: a survey (2011)Extreme learning machines: a …On the algorithmic implementation of multiclass kernel-based vector machines (2002)On the algorithmic implementa…A Unifying View of Sparse Approximate Gaussian Process Regression (2005)A Unifying View of Sparse App…CatBoost for big data: an interdisciplinary review (2020)CatBoost for big data: an int…Trends in extreme learning machines: A review (2014)Trends in extreme learning ma…Deep Learning for Anomaly Detection: A Review (2020)Deep Learning for Anomaly Det…AutoML: A survey of the state-of-the-art (2020)AutoML: A survey of the state…An insight into classification with imbalanced data: Empirical results and current trends… (2013)An insight into classificatio…Challenges in Representation Learning: A Report on Three Machine Learning Contests (2013)Challenges in Representation …
36 of 39 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.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Learning representations by back-propagating errors198631,688
A training algorithm for optimal margin classifiers199211,664
Learning Internal Representations by Error Propagation19883,036

What cites it, inside the corpus

PaperYearCited
A Tutorial on Support Vector Machines for Pattern Recognition199816,488
Nonlinear Component Analysis as a Kernel Eigenvalue Problem19988,138
Text categorization with Support Vector Machines: Learning with many relevant features19988,044
Pattern Recognition and Neural Networks19966,514
An overview of statistical learning theory19996,311
Large-Scale Machine Learning with Stochastic Gradient Descent20105,695
Extreme Learning Machine for Regression and Multiclass Classification20115,581
Learning Deep Architectures for AI20095,077
A Practical Guide to Support Vector Classication20085,074
Active Learning Literature Survey20094,788
Semi-Supervised Learning20064,334
An introduction to kernel-based learning algorithms20013,498
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases …20173,388
Prediction, Learning, and Games20063,279
Sentiment analysis algorithms and applications: A survey20143,264
Understanding Machine Learning: From Theory To Algorithms20153,081
A Short Introduction to Boosting19992,952
Support Vector Machines for Classification and Regression19982,831
A re-examination of text categorization methods19992,664
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
Choosing Multiple Parameters for Support Vector Machines20022,183
The Boosting Approach to Machine Learning: An Overview20032,023
Kernel principal component analysis19971,950
Stochastic Gradient Descent Tricks20121,944
Extreme learning machines: a survey20111,932
On the algorithmic implementation of multiclass kernel-based vector machines20021,789
A Unifying View of Sparse Approximate Gaussian Process Regression20051,782
CatBoost for big data: an interdisciplinary review20201,776
Trends in extreme learning machines: A review20141,752
Deep Learning for Anomaly Detection: A Review20201,731
AutoML: A survey of the state-of-the-art20201,705
An insight into classification with imbalanced data: Empirical results and current trends…20131,602
Challenges in Representation Learning: A Report on Three Machine Learning Contests20131,588

Links

DOI · Open access copy · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Face and Expression RecognitionComputer Science
Blind Source Separation TechniquesComputer Science

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complete

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

  • supports2 author record(s) attached.
  • supports18 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…