Vu-Linh Nguyen

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 22

Top Topics

Binary Classifiers

Ensemble Methods

Uncertainty Sampling

Top Venues

Publications

Vu-Linh Nguyen, Haifei Zhang, Sébastien Destercke
Learning Sets of Probabilities Through Ensemble Methods. ECSQARU (2023)
Vu-Linh Nguyen, Yang Yang, Cassio de Campos
Probabilistic Multi-Dimensional Classification. CoRR (2023)
Vu-Linh Nguyen, Yang Yang, Cassio de Campos
Probabilistic Multi-Dimensional Classification. UAI (2023)
Vu-Linh Nguyen, Xuan-Truong Hoang, Van-Nam Huynh
Inference Problem in Probabilistic Multi-label Classification. IUKM (2) (2023)
Yonatan Carlos Carranza Alarcón, Vu-Linh Nguyen
Skeptical inferences in multi-label ranking with sets of probabilities. CoRR (2022)
Vu-Linh Nguyen, Mohammad Hossein Shaker, Eyke Hüllermeier
How to measure uncertainty in uncertainty sampling for active learning. Mach. Learn. 111 (1) (2022)
Vu-Linh Nguyen, Eyke Hüllermeier
Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence. J. Artif. Intell. Res. 72 (2021)
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Rashad Ghassani
Racing trees to query partial data. Soft Comput. 25 (14) (2021)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
Learning Gradient Boosted Multi-label Classification Rules. CoRR (2020)
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
On Aggregation in Ensembles of Multilabel Classifiers. CoRR (2020)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD (3) (2020)
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
On Aggregation in Ensembles of Multilabel Classifiers. DS (2020)
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, Vu-Linh Nguyen, Michael Rapp
Rule-Based Multi-label Classification: Challenges and Opportunities. RuleML+RR (2020)
Vu-Linh Nguyen, Eyke Hüllermeier
Reliable Multilabel Classification: Prediction with Partial Abstention. AAAI (2020)
Vu-Linh Nguyen, Eyke Hüllermeier
Reliable Multi-label Classification: Prediction with Partial Abstention. CoRR (2019)
Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
Epistemic Uncertainty Sampling. DS (2019)
Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
Epistemic Uncertainty Sampling. CoRR (2019)
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Eyke Hüllermeier
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. IJCAI (2018)
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
Partial data querying through racing algorithms. Int. J. Approx. Reason. 96 (2018)
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
K-Nearest Neighbour Classification for Interval-Valued Data. SUM (2017)
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
Querying Partially Labelled Data to Improve a K-nn Classifier. AAAI (2017)
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
Partial Data Querying Through Racing Algorithms. IUKM (2016)