Dr Dang Nguyen

COMBAT: Alternated Training for Effective Clean-Label Backdoor Attacks

T Huynh, D Nguyen, T Pham, A Tran

(2024), Vol. 38, pp. 2436-2444, Proceedings of the AAAI Conference on Artificial Intelligence, E1

LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee's Advertisement Recommendation

D Nguyen, C Wang, Y Shen, Y Zeng

(2023), pp. 334-337, RecSys '23 : Proceedings of the 17th ACM Conference on Recommender Systems, Singapore, E1

Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction

K Nguyen, D Nguyen, N Ho

(2023), Vol. 202, pp. 26008-26030, Proceedings of the 40 th International Conference on Machine Learning, Honolulu, Hawaii, E1-1

On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks

D Nguyen, T Nguyen, K Nguyen, D Phung, H Bui, N Ho

(2023), pp. 1-5, ICASSP 2023 : Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Rhodes Island, Greece, E1-1

Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee

G Ngo, D Nguyen, D Phan-Trong, S Gupta

(2023), Vol. 222, pp. 943-958, Proceedings of Machine Learning Research, E1

Towards Effective and Robust Neural Trojan Defenses via Input Filtering

K Do, H Harikumar, H Le, D Nguyen, T Tran, S Rana, D Nguyen, W Susilo, S Venkatesh

(2022), Vol. 13665 LNCS, pp. 283-300, ECCV 2022 : Proceedings of the 17th European Conference on Computer Vision, Tel Aviv, Israel, E1

Black-Box Few-Shot Knowledge Distillation

D Nguyen, S Gupta, K Do, S Venkatesh

(2022), Vol. 13681, pp. 196-211, ECCV 2022 : Proceedings of the 17th European Conference on Computer Vision, Tel Aviv, Israel, E1

Efficient Classification with Counterfactual Reasoning and Active Learning

A Mohammed, D Nguyen, B Duong, T Nguyen

(2022), Vol. 13757, pp. 27-38, ACIIDS 2022 : Proceedings of the 14th Asian Conference on Intelligent Information and Database Systems, Ho Chi Minh City, Vietnam, E1

Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation

K Do, H Le, D Nguyen, D Nguyen, H Harikumar, T Tran, S Rana, S Venkatesh

(2022), Vol. 35, pp. 1-19, NeurIPS 2022 : Proceedings of the 36th Neural Information Processing Systems Conference 2022, New Orleans, La., E1

Bayesian Optimization with Missing Inputs

P Luong, D Nguyen, S Gupta, S Rana, S Venkatesh

(2021), Vol. 12458, pp. 691-706, ECML PKDD 2020 : Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Belgium, Ghent, E1

Factor screening using Bayesian active learning and gaussian process meta-modelling

C Li, D Nguyen, S Rana, S Gupta, A Gill, S Venkatesh

(2021), pp. 3288-3295, ICPR 2020 : Proceedings of the 25th International Conference on Pattern Recognition, Online from Milan, Italy, E1

Knowledge Distillation with Distribution Mismatch

D Nguyen, S Gupta, T Nguyen, S Rana, P Nguyen, T Tran, K Le, S Ryan, S Venkatesh

(2021), Vol. 12976, pp. 250-265, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

Fast Conditional Network Compression Using Bayesian HyperNetworks

P Nguyen, T Tran, K Le, S Gupta, S Rana, D Nguyen, T Nguyen, S Ryan, S Venkatesh

(2021), Vol. 12977, pp. 330-345, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

DeepCoDA: Personalized interpretability for compositional health data

T Quinn, D Nguyen, S Rana, S Gupta, S Venkatesh

(2020), Vol. PartF168147-11, pp. 7833-7842, ICML 2020 : Proceedings of the 37th International Conference on Machine Learning, Online, E1

Bayesian optimization for categorical and category-specific continuous inputs

D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh

(2020), pp. 5256-5263, AAAI-20 : Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence, New York, N.Y., E1

Sqn2Vec: learning sequence representation via sequential patterns with a gap constraint

D Nguyen, W Luo, T Nguyen, S Venkatesh, D Phung

(2019), Vol. 11052, pp. 569-584, ECML-PKDD 2018 : Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, Ireland, E1

Bayesian Optimization with Discrete Variables

P Luong, S Gupta, D Nguyen, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 473-484, AI 2019 : Advances in Artificial Intelligence : Proceedings of the 32nd Australian Joint Conference, Adelaide, South Australia, E1

Detection of Compromised Models Using Bayesian Optimization

D Kuttichira, S Gupta, D Nguyen, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 485-496, AI 2019 : Advances in Artificial Intelligence : Proceedings of the 32nd Australian Joint Conference, Adelaide, South Australia, E1

Learning graph representation via frequent subgraphs

D Nguyen, W Luo, T Nguyen, S Venkatesh, D Phung

(2018), Vol. PRDT18, pp. 306-314, SDM 2018 : Proceedings of the SIAM International Conference on Data Mining, San Diego, Calif., E1

Trans2Vec: Learning transaction embedding via items and frequent itemsets

D Nguyen, T Nguyen, W Luo, S Venkatesh

(2018), Vol. 10939, pp. 361-372, PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Melbourne, Victoria, E1

Exceptional contrast set mining: moving beyond the deluge of the obvious

D Nguyen, W Luo, D Phung, S Venkatesh

(2016), Vol. LNAI 9992, pp. 455-468, AI 2016 : Advances in artificial intelligence : Proceedings of the 29th Australian Joint Conference, Hobart, Tas., E1

Mining class-association rules with constraints

D Nguyen, B Vo

(2014), Vol. 245, pp. 307-318, Advances in Intelligent Systems and Computing, Hanoi, VIETNAM, E1-1

A novel method for mining class association rules with itemset constraints

D Nguyen, B Vo, B Le

(2014), Vol. 8733, pp. 494-503, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Seoul, SOUTH KOREA, E1-1