Cuong Nguyen - RankMe

21 papers A 2Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning to complement with multiple humans. Pattern Recognit. Zheng Zhang, Cuong Nguyen, Kevin Wells, Thanh-Toan Do, Gustavo Carneiro
2026	J	`jnl`	PASS: Peer-agreement based sample selection for training with instance dependent noisy labels. Image Vis. Comput. Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, Gustavo Carneiro
2025	J	`jnl`	AEON: Adaptive Estimation of Instance-Dependent In-Distribution and Out-of-Distribution Label Noise for Robust Learning. CoRR Arpit Garg, Cuong Nguyen, Rafael Felix, Yuyuan Liu, Thanh-Toan Do, Gustavo Carneiro
2025	J	`jnl`	Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models. CoRR Dung Anh Hoang, Cuong Pham, Cuong Nguyen, Trung Le, Jianfei Cai, Thanh-Toan Do
2024	J	`jnl`	Coverage-Constrained Human-AI Cooperation with Multiple Experts. CoRR Zheng Zhang, Cuong Nguyen, Kevin Wells, Thanh-Toan Do, David Rosewarne, Gustavo Carneiro
2024	—	`conf`	Instance-Dependent Noisy-Label Learning with Graphical Model Based Noise-Rate Estimation. ECCV (4) Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, Gustavo Carneiro
2023	A	`conf`	Instance-Dependent Noisy Label Learning via Graphical Modelling. WACV Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, Gustavo Carneiro
2023	J	`jnl`	Noisy-label Learning with Sample Selection based on Noise Rate Estimate. CoRR Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, Gustavo Carneiro
2023	J	`jnl`	PAC-Bayes Meta-Learning With Implicit Task-Specific Posteriors. IEEE Trans. Pattern Anal. Mach. Intell. Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2023	J	`jnl`	PASS: Peer-Agreement based Sample Selection for training with Noisy Labels. CoRR Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, Gustavo Carneiro
2023	J	`jnl`	Task Weighting in Meta-learning with Trajectory Optimisation. CoRR Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2023	J	`jnl`	Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach. CoRR Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2022	J	`jnl`	Instance-Dependent Noisy Label Learning via Graphical Modelling. CoRR Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, Gustavo Carneiro
2022	J	`jnl`	Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning. CoRR Dung Anh Hoang, Cuong Nguyen, Vasileios Belagiannis, Gustavo Carneiro
2021	J	`jnl`	Probabilistic task modelling for meta-learning. CoRR Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2021	J	`jnl`	Similarity of Classification Tasks. CoRR Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2020	J	`jnl`	PAC-Bayesian Meta-learning with Implicit Prior. CoRR Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2020	A	`conf`	Uncertainty in Model-Agnostic Meta-Learning using Variational Inference. WACV Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2020	—	`conf`	Unsupervised Task Design to Meta-Train Medical Image Classifiers. ISBI Gabriel Maicas, Cuong Nguyen, Farbod Motlagh, Jacinto C. Nascimento, Gustavo Carneiro
2019	J	`jnl`	Uncertainty in Model-Agnostic Meta-Learning using Variational Inference. CoRR Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
2019	J	`jnl`	Unsupervised Task Design to Meta-Train Medical Image Classifiers. CoRR Gabriel Maicas, Cuong Nguyen, Farbod Motlagh, Jacinto C. Nascimento, Gustavo Carneiro