We stand with Ukraine

We stand with Ukraine

Cuong Nguyen

Orcid: 0000-0003-2672-6291

Affiliations:

University of Surrey, Centre for Vision, Speech and Signal Processing (CVSSP, Guildford, UK
University of Adelaide, Australian Institute for Machine Learning (AIML), Australia

According to our database¹, Cuong Nguyen authored at least 31 papers between 2020 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

Online presence:

On csauthors.net:

Bibliography

2026

Fairness Beyond Demographics: Optimizing Performance Across Appearance-Based Hidden Cohorts in Medical Imaging.

[DOI]

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,

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Gustavo Carneiro

CoRR, May, 2026

Multi-agent decision making: A Blackwell's informativeness approach.

[DOI]

,

Cuong C. Nguyen

,

,

Gustavo Carneiro

CoRR, May, 2026

People-Centred Medical Image Analysis.

[DOI]

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,

,

,

,

David Rosewarne

,

,

,

Gustavo Carneiro

CoRR, April, 2026

Fatigue-Aware Learning to Defer via Constrained Optimisation.

[DOI]

,

Cuong C. Nguyen

,

David Rosewarne

,

,

Gustavo Carneiro

CoRR, April, 2026

Learning to complement with multiple humans.

[DOI]

,

,

,

,

Gustavo Carneiro

Pattern Recognit., 2026

PASS: Peer-agreement based sample selection for training with instance dependent noisy labels.

[DOI]

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,

,

,

Gustavo Carneiro

Image Vis. Comput., 2026

Reciprocal Teaching: Dynamic Multi-Model Teacher-Student Learning for Multiple Noisy Annotations.

[DOI]

,

Cuong C. Nguyen

,

,

Gustavo Carneiro

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026

Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models.

[DOI]

,

,

Cuong C. Nguyen

,

,

Gustavo Carneiro

,

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Coverage-Constrained Human-AI Cooperation with Multiple Experts.

[DOI]

,

Cuong C. Nguyen

,

,

,

David Rosewarne

,

Gustavo Carneiro

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models.

[DOI]

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CoRR, December, 2025

Adaptive Layer-Wise Transformations for Post-Training Quantization of Large Language Models.

[DOI]

,

,

Cuong C. Nguyen

,

,

Gustavo Carneiro

,

,

CoRR, November, 2025

Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models.

[DOI]

,

,

Cuong C. Nguyen

,

,

Gustavo Carneiro

,

CoRR, November, 2025

AEON: Adaptive Estimation of Instance-Dependent In-Distribution and Out-of-Distribution Label Noise for Robust Learning.

[DOI]

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,

,

,

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Gustavo Carneiro

CoRR, January, 2025

Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning.

[DOI]

,

Cuong C. Nguyen

,

Vasileios Belagiannis

,

,

Gustavo Carneiro

Trans. Mach. Learn. Res., 2025

Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution.

[DOI]

Cuong C. Nguyen

,

,

Gustavo Carneiro

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning.

[DOI]

,

Cuong C. Nguyen

,

,

,

Gustavo Carneiro

,

CoRR, 2024

MetaAug: Meta-data Augmentation for Post-training Quantization.

[DOI]

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,

Cuong C. Nguyen

,

,

,

Gustavo Carneiro

,

Proceedings of the Computer Vision - ECCV 2024, 2024

Instance-Dependent Noisy-Label Learning with Graphical Model Based Noise-Rate Estimation.

[DOI]

,

,

,

,

Gustavo Carneiro

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Task Weighting in Meta-learning with Trajectory Optimisation.

[DOI]

Cuong C. Nguyen

,

,

Gustavo Carneiro

Trans. Mach. Learn. Res., 2023

PAC-Bayes Meta-Learning With Implicit Task-Specific Posteriors.

[DOI]

,

,

Gustavo Carneiro

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Noisy-label Learning with Sample Selection based on Noise Rate Estimate.

[DOI]

,

,

,

,

Gustavo Carneiro

CoRR, 2023

PASS: Peer-Agreement based Sample Selection for training with Noisy Labels.

[DOI]

,

,

,

,

Gustavo Carneiro

CoRR, 2023

Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach.

[DOI]

,

,

Gustavo Carneiro

CoRR, 2023

Instance-Dependent Noisy Label Learning via Graphical Modelling.

[DOI]

,

,

,

,

Gustavo Carneiro

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning.

[DOI]

,

Cuong C. Nguyen

,

,

,

Gustavo Carneiro

,

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning.

[DOI]

,

,

Vasileios Belagiannis

,

Gustavo Carneiro

CoRR, 2022

2021

Similarity of Classification Tasks.

[DOI]

,

,

Gustavo Carneiro

CoRR, 2021

Probabilistic task modelling for meta-learning.

[DOI]

Cuong Cao Nguyen

,

,

Gustavo Carneiro

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

PAC-Bayesian Meta-learning with Implicit Prior.

[DOI]

,

,

Gustavo Carneiro

CoRR, 2020

Uncertainty in Model-Agnostic Meta-Learning using Variational Inference.

[DOI]

,

,

Gustavo Carneiro

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Unsupervised Task Design to Meta-Train Medical Image Classifiers.

[DOI]

,

,

,

Jacinto C. Nascimento

,

Gustavo Carneiro

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

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