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Journal of Machine Learning Research, ISSN 1532-4435, 2011, Volume 20, pp. 97 - 112
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 2013, Volume 30, pp. 489 - 511
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 03/2016, Volume 38, Issue 3, pp. 447 - 461
Journal Article
Pattern Recognition, ISSN 0031-3203, 03/2016, Volume 51, pp. 463 - 480
Mislabeled examples in the training data can severely affect the performance of supervised classifiers. In this paper, we present an approach to remove any... 
Support vectors | Mislabeled examples | Label noise | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Information Sciences, ISSN 0020-0255, 04/2019, Volume 479, pp. 135 - 152
In any knowledge discovery process the value of extracted knowledge is directly related to the quality of the data used. Big Data problems, generated by... 
Big Data | Smart Data | Label noise | Classification | Class noise | ENSEMBLE | COMPUTER SCIENCE, INFORMATION SYSTEMS | MAPREDUCE | TRENDS | CHALLENGES
Journal Article
Neurocomputing, ISSN 0925-2312, 02/2019, Volume 330, pp. 138 - 150
Distance metric learning aims to learn a metric with the similarity of samples. However, the increasing scalability and complexity of dataset or complex... 
KISSME | Resampling scheme | Label noise | Distance metric learning | PERSON REIDENTIFICATION | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
BMC genomics, ISSN 1471-2164, 12/2019, Volume 20, Issue Suppl 9, pp. 913 - 10
Single-cell RNA-sequencing (scRNA-seq) is a fast emerging technology allowing global transcriptome profiling on the single cell level. Cell type identification... 
RNA | Developmental biology | Analysis | scRNA-seq | Cell type classification | Class label noise | Single-cell RNA-seq
Journal Article
Computer Vision and Image Understanding, ISSN 1077-3142, 11/2019, Volume 188, p. 102782
Supervised classification of remotely sensed images is a classical method for change detection. The task requires training data containing images with known... 
Random forest | Change detection | Label noise | Supervised classification | IMAGE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 04/2018, Volume 18, pp. 1 - 33
We study binary classification in the presence of class-conditional random noise, where the learner gets to see labels that are flipped independently with some... 
Statistical consistency | Class-conditional label noise | Cost-sensitive learning | PERCEPTRONS | class-conditional label noise | statistical consistency | cost-sensitive learning | CLASSIFICATION | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 03/2018, Volume 27, Issue 3, pp. 1542 - 1553
Distance metric learning (DML) has achieved great success in many computer vision tasks. However, most existing DML algorithms are based on point estimation,... 
Training | Stochastic processes | Distance metric learning | label noise | Robustness | Inference algorithms | Bayes methods | Noise measurement | generalization error | bayesian inference | Bayesian inference | Bayes' theorem | Usage | Algorithms
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 6/2019, pp. 1 - 1
In this paper, we study weakly supervised learning where a large amount of label information is not accessible. This includes incomplete supervision such as... 
multi-instance learning | Performance gain | label noise learning | Proposals | weakly supervised learning | Task analysis | Supervised learning | Training data | Machine learning | Semisupervised learning | safe | semi-supervised learning | domain adaptation
Journal Article
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 9/2019, pp. 1 - 15
Practical data sets often contain the label noise caused by various human factors or measurement errors, which means that a fraction of training examples might... 
Training | Computer science | Learning systems | matrix recovery | Classification | generalization bound | side information | label noise | Noise measurement | Matrix decomposition | Risk management | Task analysis
Journal Article
Neurocomputing, ISSN 0925-2312, 07/2015, Volume 160, pp. 93 - 107
In many applications, the training data, from which one needs to learn a classifier, is corrupted with label noise. Many standard algorithms such as SVM... 
Loss function | Risk minimization | Noise tolerance | Label noise | Classification | PERCEPTRON | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Electrical engineering | Algorithms | Computer Science - Learning
Journal Article
2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 10/2019, pp. 16 - 20
Label noise is emerging as a pressing issue in sound event classification. This arises as we move towards larger datasets that are difficult to annotate... 
loss function | mixup | label noise | label smoothing | Sound event classification
Conference Proceeding
Knowledge-Based Systems, ISSN 0950-7051, 09/2017, Volume 132, pp. 144 - 155
To deal with the uncertainty, vagueness and overlapping distribution within the data sets, a novel incremental fuzzy cluster ensemble method based on rough set... 
Cluster ensemble | Granular computing | Rough sets | Random forests | CONSENSUS | LABEL NOISE | MODEL | CATEGORICAL-DATA | OUTLIERS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Computer science | Information science | Analysis | Machine learning
Journal Article
Neurocomputing, ISSN 0925-2312, 07/2015, Volume 160, pp. 108 - 119
Noisy data are common in real-world problems and may have several causes, like inaccuracies, distortions or contamination during data collection, storage... 
Noise Filter | Complexity measures | Label noise | Classification | REPOSITORY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms
Journal Article
JOURNAL OF MACHINE LEARNING RESEARCH, ISSN 1532-4435, 2019, Volume 20
Many machine learning problems can be characterized by mutual contamination models. In these problems, one observes several random samples from different... 
mixed membership models | multiclass classification with label noise | classification with partial labels | topic modeling | mutual contamination models | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Neurocomputing, ISSN 0925-2312, 07/2015, Volume 160, pp. 53 - 62
Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties... 
Support vector machines | Label flip attacks | Adversarial learning | Label noise | ROBUSTNESS | SECURITY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Computer science | Algorithms | Data mining | Analysis | Machine learning
Journal Article
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