Who Cited It

Classification in the Presence of Label Noise: A Survey

2014 · IEEE Transactions on Neural Networks and Learning Systems · 1,777 citations · 2 from inside this corpus

Benoît Frénay‬, Michel Verleysen

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.

Classification in the Presence of Label Noise: A Survey (2014)Classification in the Presenc…Random Forests (2001)Random ForestsInduction of Decision Trees (1986)Induction of Decision TreesInduction of decision trees (1986)Induction of decision treesAnomaly detection (2009)Anomaly detectionA Mathematical Theory of Evidence (1976)A Mathematical Theory of Evid…Experiments with a new boosting algorithm (1996)Experiments with a new boosti…Building a Large Annotated Corpus of English: The Penn Treebank (1993)Building a Large Annotated Co…Survey of Clustering Algorithms (2005)Survey of Clustering Algorith…Estimating the Support of a High-Dimensional Distribution (2001)Estimating the Support of a H…Combining labeled and unlabeled data with co-training (1998)Combining labeled and unlabel…Instance-Based Learning Algorithms (1991)Instance-Based Learning Algor…A Survey of Outlier Detection Methodologies (2004)A Survey of Outlier Detection…Popular Ensemble Methods: An Empirical Study (1999)Popular Ensemble Methods: An …An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:… (2000)An Experimental Comparison of…A Short Introduction to Boosting (1999)A Short Introduction to Boost…Pattern recognition : a statistical approach (1982)Pattern recognition : a stati…Instance-based learning algorithms (1991)Instance-based learning algor…Applied Linear Regression (1987)Applied Linear RegressionA fuzzy K-nearest neighbor algorithm (1985)A fuzzy K-nearest neighbor al…RCV1: A New Benchmark Collection for Text Categorization Research (2004)RCV1: A New Benchmark Collect…Improved boosting algorithms using confidence-rated predictions (1998)Improved boosting algorithms …Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…Support Vector Method for Novelty Detection (1999)Support Vector Method for Nov…Improved Boosting Algorithms Using Confidence-rated Predictions (1999)Improved Boosting Algorithms …Cheap and fast---but is it good? (2008)Cheap and fast---but is it go…A brief introduction to weakly supervised learning (2017)A brief introduction to weakl…Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach (2017)
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What this paper cites, inside the corpus

PaperYearCited
Random Forests2001131,109
Induction of Decision Trees198615,020
Induction of decision trees198612,427
Anomaly detection200911,511
A Mathematical Theory of Evidence19768,967
Experiments with a new boosting algorithm19967,582
Building a Large Annotated Corpus of English: The Penn Treebank19937,538
Survey of Clustering Algorithms20056,210
Estimating the Support of a High-Dimensional Distribution20016,097
Combining labeled and unlabeled data with co-training19985,631
Instance-Based Learning Algorithms19914,128
A Survey of Outlier Detection Methodologies20043,382
Popular Ensemble Methods: An Empirical Study19992,988
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…20002,962
A Short Introduction to Boosting19992,952
Pattern recognition : a statistical approach19822,927
Instance-based learning algorithms19912,917
Applied Linear Regression19872,858
A fuzzy K-nearest neighbor algorithm19852,679
RCV1: A New Benchmark Collection for Text Categorization Research20042,604
Improved boosting algorithms using confidence-rated predictions19982,573
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
Support Vector Method for Novelty Detection19992,067
Improved Boosting Algorithms Using Confidence-rated Predictions19991,966
Cheap and fast---but is it good?20081,928

What cites it, inside the corpus

PaperYearCited
A brief introduction to weakly supervised learning20171,911
Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach20171,464

Links

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Topics

Machine Learning and Data ClassificationComputer Science
Industrial Vision Systems and Defect DetectionEngineering
Advanced Multi-Objective Optimization AlgorithmsComputer Science

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  • supports2 author record(s) attached.
  • supports395 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:53+00:00.

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