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ORCIDLIDTA 2022: Grenoble, France
- Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA 2022, Grenoble, France, September 23, 2022. Proceedings of Machine Learning Research 183, PMLR 2022
Preface
- Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
4th Workshop on Learning with Imbalanced Domains: Preface. 1-7
Long Papers
- Ioannis Antoniadis, Vincent Vercruyssen, Jesse Davis:
Systematic Evaluation of CASH Search Strategies for Unsupervised Anomaly Detection. 8-22 - Sander De Block, Jessa Bekker:
Bagging Propensity Weighting: A Robust method for biased PU Learning. 23-37 - Xin Yue Song, Nam Dao, Paula Branco:
DistSMOGN: Distributed SMOGN for Imbalanced Regression Problems. 38-52 - Carlos Ortega Vázquez, Jochen De Weerdt, Seppe vanden Broucke:
The Hidden Cost of Fraud: An Instance-Dependent Cost-Sensitive Approach for Positive and Unlabeled Learning. 53-67 - Yiwen Shi, Taha ValizadehAslani, Jing Wang, Ping Ren, Yi Zhang, Meng Hu, Liang Zhao, Hualou Liang:
Improving Imbalanced Learning by Pre-finetuning with Data Augmentation. 68-82 - Jairo da Silva Freitas Junior, Paulo Henrique Pisani:
Performance and model complexity on imbalanced datasets using resampling and cost-sensitive algorithms. 83-97 - Adam Wojciechowski, Mateusz Lango
:
Adversarial oversampling for multi-class imbalanced data classification with convolutional neural networks. 98-111 - Thomas Bonnier, Benjamin Bosch:
Assessing the Robustness of Ordinal Classifiers against Imbalanced and Shifting Distributions. 112-126
Short Papers
- Ellen Rushe, Brian Mac Namee:
Deep Contextual Novelty Detection with Context Prediction. 127-138 - Baptiste Bauvin, Jacques Corbeil, Dominique Benielli, Sokol Koço, Cécile Capponi:
Integrating and reporting full multi-view supervised learning experiments using SuMMIT. 139-150 - Solander Patricio Lopes Agostinho, João Mendes-Moreira:
Probabilistic Metric to measure the imbalance in multi-class problems. 151-162 - Aymene Mohammed Bouayed, Samuel Deslauriers-Gauthier, Mauro Zucchelli, Rachid Deriche:
CNN and diffusion MRI’s 4th degree rotational invariants for Alzheimer’s disease identification. 163-174 - Joanna Komorniczak, Pawel Ksieniewicz, Michal Wozniak:
Data complexity and classification accuracy correlation in oversampling algorithms. 175-186 - Agnieszka Lipska, Jerzy Stefanowski:
The Influence of Multiple Classes on Learning from Imbalanced Data Streams. 187-198
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