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Editors: Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang
4th Workshop on Learning with Imbalanced Domains: Preface
; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:1-7
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Systematic Evaluation of CASH Search Strategies for Unsupervised Anomaly Detection
Ioannis Antoniadis, Vincent Vercruyssen, Jesse Davis; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:8-22
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Bagging Propensity Weighting: A Robust method for biased PU Learning
Sander De Block, Jessa Bekker; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:23-37
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DistSMOGN: Distributed SMOGN for Imbalanced Regression Problems
Xin Yue Song, Nam Dao, Paula Branco; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:38-52
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The Hidden Cost of Fraud: An Instance-Dependent Cost-Sensitive Approach for Positive and Unlabeled Learning
Carlos Ortega Vasquez, Jochen De Weerdt, Seppe vanden Broucke; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:53-67
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Improving Imbalanced Learning by Pre-finetuning with Data Augmentation
Yiwen Shi, Taha ValizadehAslani, Jing Wang, Ping Ren, Yi Zhang, Meng Hu, Liang Zhao, Hualou Liang; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:68-82
Performance and model complexity on imbalanced datasets using resampling and cost-sensitive algorithms
Jairo da Silva Freitas Junior, Paulo Henrique Pisani; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:83-97
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Adversarial oversampling for multi-class imbalanced data classification with convolutional neural networks
Adam Wojciechowski, Mateusz Lango; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:98-111
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Assessing the Robustness of Ordinal Classifiers against Imbalanced and Shifting Distributions
Thomas Bonnier, Benjamin Bosch; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:112-126
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Deep Contextual Novelty Detection with Context Prediction
Ellen Rushe, Brian Mac Namee; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:127-138
Integrating and reporting full multi-view supervised learning experiments using SuMMIT
Baptiste Bauvin, Jacques Corbeil, Dominique Benielli, Sokol Koço, Cecile Capponi; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:139-150
Probabilistic Metric to measure the imbalance in multi-class problems
Solander Patricio Lopes Agostinho, João Mendes-Moreira; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:151-162
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CNN and diffusion MRI’s 4th degree rotational invariants for Alzheimer’s disease identification
Aymene Mohammed Bouayed, Samuel Deslauriers-Gauthier, Mauro Zucchelli, Rachid Deriche; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:163-174
Data complexity and classification accuracy correlation in oversampling algorithms
Joanna Komorniczak, Paweł Ksieniewicz, Michał Woźniak; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:175-186
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The Influence of Multiple Classes on Learning from Imbalanced Data Streams
Agnieszka Lipska, Jerzy Stefanowski; Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 183:187-198
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