Who Cited It

Ensembling neural networks: Many could be better than all

2002 · Artificial Intelligence · 1,990 citations · 3 from inside this corpus

Zhi‐Hua Zhou, Jianxin Wu, Wei Tang

No abstract in the source record.

Ensembling neural networks: Many could be better than all (2002)Ensembling neural networks: M…Genetic algorithms in search, optimization, and machine learning (1989)Genetic algorithms in search,…Bagging Predictors (1996)Bagging PredictorsBagging predictors (1996)Bagging predictorsLearning Internal Representations by Error Propagation (1985)Learning Internal Representat…Genetic Algorithms (2002)Genetic AlgorithmsUCI Repository of machine learning databases (1998)UCI Repository of machine lea…Stacked generalization (1992)Stacked generalizationExperiments with a new boosting algorithm (1996)Experiments with a new boosti…Adaptive Mixtures of Local Experts (1991)Adaptive Mixtures of Local Ex…Neural network ensembles (1990)Neural network ensemblesNeural Networks and the Bias/Variance Dilemma (1992)Neural Networks and the Bias/…The Strength of Weak Learnability (1990)The Strength of Weak Learnabi…Popular Ensemble Methods: An Empirical Study (1999)Popular Ensemble Methods: An …Hierarchical Mixtures of Experts and the EM Algorithm (1994)Hierarchical Mixtures of Expe…An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia… (1999)An Empirical Comparison of Vo…The strength of weak learnability (1990)The strength of weak learnabi…Neural Network Ensembles, Cross Validation, and Active Learning (1994)Neural Network Ensembles, Cro…Boosting a Weak Learning Algorithm by Majority (1995)Boosting a Weak Learning Algo…Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Langu… (2022)Pre-train, Prompt, and Predic…Ensemble learning: A survey (2018)Ensemble learning: A surveyA survey on ensemble learning (2019)A survey on ensemble learning
21 of 21 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
Genetic algorithms in search, optimization, and machine learning198949,344
Bagging Predictors199617,191
Bagging predictors199616,468
Learning Internal Representations by Error Propagation198516,273
Genetic Algorithms200216,154
UCI Repository of machine learning databases199810,546
Stacked generalization19927,777
Experiments with a new boosting algorithm19967,582
Adaptive Mixtures of Local Experts19915,234
Neural network ensembles19904,288
Neural Networks and the Bias/Variance Dilemma19923,612
The Strength of Weak Learnability19903,344
Popular Ensemble Methods: An Empirical Study19992,988
Hierarchical Mixtures of Experts and the EM Algorithm19942,684
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…19992,656
The strength of weak learnability19902,477
Neural Network Ensembles, Cross Validation, and Active Learning19941,803
Boosting a Weak Learning Algorithm by Majority19951,691

What cites it, inside the corpus

PaperYearCited
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Langu…20223,836
Ensemble learning: A survey20183,088
A survey on ensemble learning20191,951

Links

DOI · OpenAlex record

Topics

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

Is this record sound?

complete

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

  • supports3 author record(s) attached.
  • supports65 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 2026-09-04T03:58:51+00:00.

sha256 6e314d9c6052d1ed…