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ORCIDVu-Linh Nguyen
Person information
- affiliation: Paderborn University, Heinz Nixdorf Institute, Germany
- affiliation (PhD): University of Technology of Compiègne, Heudiasyc Laboratory, France
- affiliation: Japan Advanced Institute of Science and Technology, Nomi, Japan
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Books and Theses
- 2018
[b1]Vu-Linh Nguyen:
Imprecision in machine learning problems. (Imprécision en apprentissage statistique). University of Technology of Compiègne, France, 2018
Journal Articles
- 2025
- [j5]Vu-Linh Nguyen, Haifei Zhang, Sébastien Destercke:
Credal ensembling in multi-class classification. Mach. Learn. 114(1): 19 (2025) - 2022
- [j4]Vu-Linh Nguyen
, Mohammad Hossein Shaker, Eyke Hüllermeier:
How to measure uncertainty in uncertainty sampling for active learning. Mach. Learn. 111(1): 89-122 (2022) - 2021
- [j3]Vu-Linh Nguyen, Eyke Hüllermeier:
Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence. J. Artif. Intell. Res. 72: 613-665 (2021) - [j2]Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Rashad Ghassani:
Racing trees to query partial data. Soft Comput. 25(14): 9285-9305 (2021) - 2018
- [j1]Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson:
Partial data querying through racing algorithms. Int. J. Approx. Reason. 96: 36-55 (2018)
Conference and Workshop Papers
- 2024
- [c14]Salvador Madrigal, Vu-Linh Nguyen, Cyprien Gilet, Sébastien Destercke:
Discrete Minimax Binary Relevance Classifier for Imbalanced Multi-label Classification. SUM 2024: 281-296 - [c13]Vu-Linh Nguyen, Toan Nguyen Mau, Van-Nam Huynh:
Accelerate K-Mode Algorithms Using The Triangle Inequality. SUM 2024: 325-339 - 2023
- [c12]Vu-Linh Nguyen, Haifei Zhang, Sébastien Destercke:
Learning Sets of Probabilities Through Ensemble Methods. ECSQARU 2023: 270-283 - [c11]Vu-Linh Nguyen, Xuan-Truong Hoang, Van-Nam Huynh:
Inference Problem in Probabilistic Multi-label Classification. IUKM (2) 2023: 3-14 - [c10]Vu-Linh Nguyen, Yang Yang, Cassio de Campos:
Probabilistic Multi-Dimensional Classification. UAI 2023: 1522-1533 - 2020
- [c9]Vu-Linh Nguyen, Eyke Hüllermeier:
Reliable Multilabel Classification: Prediction with Partial Abstention. AAAI 2020: 5264-5271 - [c8]Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz:
On Aggregation in Ensembles of Multilabel Classifiers. DS 2020: 533-547 - [c7]Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier:
Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD (3) 2020: 124-140 - [c6]Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, Vu-Linh Nguyen, Michael Rapp:
Rule-Based Multi-label Classification: Challenges and Opportunities. RuleML+RR 2020: 3-19 - 2019
- [c5]Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier:
Epistemic Uncertainty Sampling. DS 2019: 72-86 - 2018
- [c4]Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Eyke Hüllermeier:
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. IJCAI 2018: 5089-5095 - 2017
- [c3]Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson:
Querying Partially Labelled Data to Improve a K-nn Classifier. AAAI 2017: 2401-2407 - [c2]Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson:
K-Nearest Neighbour Classification for Interval-Valued Data. SUM 2017: 93-106 - 2016
- [c1]Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson:
Partial Data Querying Through Racing Algorithms. IUKM 2016: 163-174
Parts in Books or Collections
- 2015
- [p1]Vu-Linh Nguyen, Van-Nam Huynh:
Using Conditional Copula to Estimate Value-at-Risk in Vietnam's Foreign Exchange Market. Econometrics of Risk 2015: 471-482
Informal and Other Publications
- 2023
- [i6]Vu-Linh Nguyen, Yang Yang, Cassio de Campos:
Probabilistic Multi-Dimensional Classification. CoRR abs/2306.06517 (2023) - 2022
- [i5]Yonatan Carlos Carranza Alarcón, Vu-Linh Nguyen:
Skeptical inferences in multi-label ranking with sets of probabilities. CoRR abs/2210.08576 (2022) - 2020
- [i4]Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz:
On Aggregation in Ensembles of Multilabel Classifiers. CoRR abs/2006.11916 (2020) - [i3]Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier:
Learning Gradient Boosted Multi-label Classification Rules. CoRR abs/2006.13346 (2020) - 2019
- [i2]Vu-Linh Nguyen, Eyke Hüllermeier:
Reliable Multi-label Classification: Prediction with Partial Abstention. CoRR abs/1904.09235 (2019) - [i1]Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier:
Epistemic Uncertainty Sampling. CoRR abs/1909.00218 (2019)
Coauthor Index
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