Vu-Linh Nguyen

34 papers A* 3A 1B 3C 3Journal 13Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Srnc: semi-supervised learning for robust novel cell-type identification in single cell RNA sequencing data.
BMC Bioinform.
Thi Van Nguyen, Van Hoan Do, Vu-Linh Nguyen
2025 J jnl
Credal ensembling in multi-class classification.
Mach. Learn.
Vu-Linh Nguyen, Haifei Zhang, Sébastien Destercke
2025 C conf
Discrete Minimax Probabilistic Classifier Chains for Multi-label Classification Under Label Imbalance.
ECSQARU
Salvador Madrigal, Cyprien Gilet, Vu-Linh Nguyen, Sébastien Destercke
2025 — conf
Robust Classification in Bayesian Neural Networks.
IUKM (1)
Kim-Dung Tran, Xuan-Truong Hoang, Vu-Linh Nguyen, Sébastien Destercke, Van-Nam Huynh
2025 J jnl
Robust Explanations Through Uncertainty Decomposition: A Path to Trustworthier AI.
CoRR
Chenrui Zhu, Louenas Bounia, Vu-Linh Nguyen, Sébastien Destercke, Arthur Hoarau
2025 C conf
Robust Explanations: The Case of Prime Implicants.
ECSQARU
Chenrui Zhu, Vu-Linh Nguyen, Marie-Hélène Masson, Sébastien Destercke
2025 — conf
Self-explaining Neural Network for Multi-criteria Sentiment Analysis.
IUKM (1)
Xuan-Truong Hoang, Vu-Linh Nguyen, Takayuki Kitagawa, Van-Nam Huynh
2024 — conf
Accelerate K-Mode Algorithms Using The Triangle Inequality.
SUM
Vu-Linh Nguyen, Toan Nguyen Mau, Van-Nam Huynh
2024 — conf
Discrete Minimax Binary Relevance Classifier for Imbalanced Multi-label Classification.
SUM
Salvador Madrigal, Vu-Linh Nguyen, Cyprien Gilet, Sébastien Destercke
2024 — conf
Towards A Wearable Passive Lower-Limb Exoskeleton Based on the Compact Gear-Spring Mechanism.
ROBIO
Quang Phuoc Minh Pham, Hung Quang Nguyen, Quan Minh Vo, Tien Dac Lai, Hien Vu Thu Nguyen, Vu-Linh Nguyen
2023 — conf
Inference Problem in Probabilistic Multi-label Classification.
IUKM (2)
Vu-Linh Nguyen, Xuan-Truong Hoang, Van-Nam Huynh
2023 C conf
Learning Sets of Probabilities Through Ensemble Methods.
ECSQARU
Vu-Linh Nguyen, Haifei Zhang, Sébastien Destercke
2023 A conf
Probabilistic Multi-Dimensional Classification.
UAI
Vu-Linh Nguyen, Yang Yang, Cassio de Campos
2023 J jnl
Probabilistic Multi-Dimensional Classification.
CoRR
Vu-Linh Nguyen, Yang Yang, Cassio de Campos
2022 J jnl
How to measure uncertainty in uncertainty sampling for active learning.
Mach. Learn.
Vu-Linh Nguyen, Mohammad Hossein Shaker, Eyke Hüllermeier
2022 J jnl
Skeptical inferences in multi-label ranking with sets of probabilities.
CoRR
Yonatan Carlos Carranza Alarcón, Vu-Linh Nguyen
2021 J jnl
Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence.
J. Artif. Intell. Res.
Vu-Linh Nguyen, Eyke Hüllermeier
2021 J jnl
Racing trees to query partial data.
Soft Comput.
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Rashad Ghassani
2020 — conf
Learning Gradient Boosted Multi-label Classification Rules.
ECML/PKDD (3)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
2020 J jnl
Learning Gradient Boosted Multi-label Classification Rules.
CoRR
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
2020 B conf
On Aggregation in Ensembles of Multilabel Classifiers.
DS
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2020 J jnl
On Aggregation in Ensembles of Multilabel Classifiers.
CoRR
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2020 A* conf
Reliable Multilabel Classification: Prediction with Partial Abstention.
AAAI
Vu-Linh Nguyen, Eyke Hüllermeier
2020 B conf
Rule-Based Multi-label Classification: Challenges and Opportunities.
RuleML+RR
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, Vu-Linh Nguyen, Michael Rapp
2019 B conf
Epistemic Uncertainty Sampling.
DS
Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
2019 J jnl
Epistemic Uncertainty Sampling.
CoRR
Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
2019 J jnl
Reliable Multi-label Classification: Prediction with Partial Abstention.
CoRR
Vu-Linh Nguyen, Eyke Hüllermeier
2018 — —
Imprecision in machine learning problems. (Imprécision en apprentissage statistique).
Vu-Linh Nguyen
2018 J jnl
Partial data querying through racing algorithms.
Int. J. Approx. Reason.
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
2018 A* conf
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty.
IJCAI
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Eyke Hüllermeier
2017 — conf
K-Nearest Neighbour Classification for Interval-Valued Data.
SUM
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
2017 A* conf
Querying Partially Labelled Data to Improve a K-nn Classifier.
AAAI
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
2016 — conf
Partial Data Querying Through Racing Algorithms.
IUKM
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson
2015 — ch.
Using Conditional Copula to Estimate Value-at-Risk in Vietnam's Foreign Exchange Market.
Econometrics of Risk
Vu-Linh Nguyen, Van-Nam Huynh