Who Cited It

Boosting the margin: a new explanation for the effectiveness of voting methods

1998 · The Annals of Statistics · 2,344 citations · 20 from inside this corpus

Peter L. Bartlett, Yoav Freund, Wee Sun Lee low, Robert E. Schapire

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.

Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…Support-vector networks (1995)Support-vector networksThe Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Support-Vector Networks (1995)Support-Vector NetworksBagging Predictors (1996)Bagging PredictorsA training algorithm for optimal margin classifiers (1992)A training algorithm for opti…UCI Repository of machine learning databases (1998)UCI Repository of machine lea…Experiments with a new boosting algorithm (1996)Experiments with a new boosti…The Strength of Weak Learnability (1990)The Strength of Weak Learnabi…An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:… (2000)An Experimental Comparison of…Universal approximation bounds for superpositions of a sigmoidal function (1993)Universal approximation bound…Solving Multiclass Learning Problems via Error-Correcting Output Codes (1995)Solving Multiclass Learning P…Improved boosting algorithms using confidence-rated predictions (1998)Improved boosting algorithms …The strength of weak learnability (1990)The strength of weak learnabi…On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities (1971)On the Uniform Convergence of…UCI Repository of Machine Learning Databases (1996)UCI Repository of Machine Lea…Boosting a Weak Learning Algorithm by Majority (1995)What Size Net Gives Valid Generalization? (1989)What Size Net Gives Valid Gen…Random Forests (2001)Random ForestsOn combining classifiers (1998)On combining classifiersAn introduction to kernel-based learning algorithms (2001)An introduction to kernel-bas…Popular Ensemble Methods: An Empirical Study (1999)Popular Ensemble Methods: An …Ensemble based systems in decision making (2006)Ensemble based systems in dec…A Short Introduction to Boosting (1999)A Short Introduction to Boost…An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia… (1999)An Empirical Comparison of Vo…Improved boosting algorithms using confidence-rated predictions (1998)Improved boosting algorithms …BoosTexter: A Boosting-based System for Text Categorization (2000)BoosTexter: A Boosting-based …Ensemble deep learning: A review (2022)Ensemble deep learning: A rev…Rademacher and Gaussian Complexities: Risk Bounds and Structural Results (2001)Rademacher and Gaussian Compl…The Boosting Approach to Machine Learning: An Overview (2003)The Boosting Approach to Mach…Improved Boosting Algorithms Using Confidence-rated Predictions (1999)Improved Boosting Algorithms …Multi-class AdaBoost (2009)Multi-class AdaBoostRotation Forest: A New Classifier Ensemble Method (2006)Classification in the Presence of Label Noise: A Survey (2014)Reconciling modern machine-learning practice and the classical bias–variance trade-off (2019)Reconciling modern machine-le…Quantile Regression Forests (2006)Quantile Regression ForestsInductive learning algorithms and representations for text categorization (1998)Inductive learning algorithms…
36 of 37 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

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

What this paper cites, inside the corpus

PaperYearCited
Support-vector networks199541,028
The Nature of Statistical Learning Theory199539,409
Support-Vector Networks199533,914
Bagging Predictors199617,191
A training algorithm for optimal margin classifiers199211,664
UCI Repository of machine learning databases199810,546
Experiments with a new boosting algorithm19967,582
The Strength of Weak Learnability19903,344
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…20002,962
Universal approximation bounds for superpositions of a sigmoidal function19932,880
Solving Multiclass Learning Problems via Error-Correcting Output Codes19952,729
Improved boosting algorithms using confidence-rated predictions19982,573
The strength of weak learnability19902,477
On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities19712,435
UCI Repository of Machine Learning Databases19962,343
Boosting a Weak Learning Algorithm by Majority19951,691
What Size Net Gives Valid Generalization?19891,559

What cites it, inside the corpus

PaperYearCited
Random Forests2001131,109
On combining classifiers19985,302
An introduction to kernel-based learning algorithms20013,498
Popular Ensemble Methods: An Empirical Study19992,988
Ensemble based systems in decision making20062,965
A Short Introduction to Boosting19992,952
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…19992,656
Improved boosting algorithms using confidence-rated predictions19982,573
BoosTexter: A Boosting-based System for Text Categorization20002,200
Ensemble deep learning: A review20222,136
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results20012,126
The Boosting Approach to Machine Learning: An Overview20032,023
Improved Boosting Algorithms Using Confidence-rated Predictions19991,966
Multi-class AdaBoost20091,916
Rotation Forest: A New Classifier Ensemble Method20061,911
Classification in the Presence of Label Noise: A Survey20141,777
Reconciling modern machine-learning practice and the classical bias–variance trade-off20191,561
Quantile Regression Forests20061,506
Inductive learning algorithms and representations for text categorization19981,469

Links

Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record

Topics

Imbalanced Data Classification TechniquesComputer Science
Machine Learning and AlgorithmsComputer Science
Advanced Bandit Algorithms ResearchDecision Sciences

Is this record sound?

complete

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

  • supports4 author record(s) attached.
  • supports47 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 2026-09-04T03:58:49+00:00.

sha256 a2172c1bbe00c44b…