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ORCIDDinh Q. Phung
Dinh Quoc Phung – Dinh Phung 0001
Person information
- affiliation: Monash University, Melbourne, Victoria, Australia
- affiliation: Deakin University, Center of Pattern Recognition and Data Analytics, Australia
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2020 – today
- 2023
[j62]Hung Bui, Nguyen Minh Le, Dat Quoc Nguyen, Linh Pham, Dinh Q. Phung:
Building and Nurturing AI Development in Vietnam. Commun. ACM 66(7): 75-76 (2023)- [j61]Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai:
Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing 555: 126605 (2023) - [c233]Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung:
Global-Local Regularization Via Distributional Robustness. AISTATS 2023: 7644-7664 - [c232]Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen:
Two-View Graph Neural Networks for Knowledge Graph Completion. ESWC 2023: 262-278 - [c231]Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Reza Haf, Seyit Camtepe, Dinh Phung:
An Additive Instance-Wise Approach to Multi-class Model Interpretation. ICLR 2023 - [c230]Son Duy Dao, Dat Huynh, He Zhao, Dinh Phung, Jianfei Cai:
Open-Vocabulary Multi-label Image Classification with Pretrained Vision-Language Model. ICME 2023: 2135-2140 - [c229]Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung:
Vector Quantized Wasserstein Auto-Encoder. ICML 2023: 35223-35242 - [c228]Thien Hai Nguyen, Thinh Pham, Khoi Minh Le, Manh Luong, Nguyen Luong Tran, Hieu Man, Dang Minh Nguyen, Tuan Anh Luu, Thien Huu Nguyen, Hung Bui, Dinh Phung, Dat Quoc Nguyen:
A Vietnamese Spelling Correction System. IUI Companion 2023: 158-161 - [c227]Vy Vo
, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung:
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. KDD 2023: 2211-2222 - [c226]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung:
Adversarial local distribution regularization for knowledge distillation. WACV 2023: 4670-4679 - [i108]Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai:
Class Enhancement Losses with Pseudo Labels for Zero-shot Semantic Segmentation. CoRR abs/2301.07336 (2023) - [i107]Van-Anh Nguyen, Long Tung Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le:
Flat Seeking Bayesian Neural Networks. CoRR abs/2302.02713 (2023) - [i106]Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung:
Vector Quantized Wasserstein Auto-Encoder. CoRR abs/2302.05917 (2023) - [i105]Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Q. Phung:
Hyperbolic Geometry in Computer Vision: A Survey. CoRR abs/2304.10764 (2023) - [i104]Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Q. Phung:
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. CoRR abs/2304.13229 (2023) - [i103]Thuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza Haffari:
Active Continual Learning: Labelling Queries in a Sequence of Tasks. CoRR abs/2305.03923 (2023) - [i102]Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Q. Phung, Trung Le:
Sharpness & Shift-Aware Self-Supervised Learning. CoRR abs/2305.10252 (2023) - [i101]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin Bonilla, Dinh Q. Phung:
Learning Directed Graphical Models with Optimal Transport. CoRR abs/2305.15927 (2023) - [i100]Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Yuki Kume, Van Nguyen, Dinh Phung, John C. Grundy:
AIBugHunter: A Practical Tool for Predicting, Classifying and Repairing Software Vulnerabilities. CoRR abs/2305.16615 (2023) - [i99]Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung:
Optimal Transport Model Distributional Robustness. CoRR abs/2306.04178 (2023) - [i98]Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Q. Phung:
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities. CoRR abs/2306.06109 (2023) - [i97]Xiaohao Yang, He Zhao, Dinh Phung, Lan Du:
Towards Generalising Neural Topical Representations. CoRR abs/2307.12564 (2023) - 2022
- [j60]Trung Le, Khanh Nguyen, Dinh Q. Phung:
Improving kernel online learning with a snapshot memory. Mach. Learn. 111(3): 997-1018 (2022) - [j59]Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Geoffrey I. Webb, Dinh Phung:
Robust Variational Learning for Multiclass Kernel Models With Stein Refinement. IEEE Trans. Knowl. Data Eng. 34(9): 4425-4438 (2022) - [c225]Thuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza Haffari:
Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out Training. ACL (Findings) 2022: 582-588 - [c224]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung:
Particle-based Adversarial Local Distribution Regularization. AISTATS 2022: 5212-5224 - [c223]Tam Le, Truyen Nguyen, Dinh Phung, Viet Anh Nguyen:
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. AISTATS 2022: 9844-9868 - [c222]Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Hung Tran, Dinh Q. Phung:
On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds. AISTATS 2022: 11438-11460 - [c221]Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung:
Bridging Global Context Interactions for High-Fidelity Image Completion. CVPR 2022: 11502-11512 - [c220]Linh Vu, Raphaël C.-W. Phan, Lim Wern Han, Dinh Phung:
Improved speech emotion recognition based on music-related audio features. EUSIPCO 2022: 120-124 - [c219]Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung:
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR 2022 - [c218]Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho:
On Transportation of Mini-batches: A Hierarchical Approach. ICML 2022: 16622-16655 - [c217]Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Phung:
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection. ICSE-Companion 2022: 178-182 - [c216]Tuan-Duy H. Nguyen, Duy Phung, Duy Tran-Cong Nguyen, Hieu Minh Tran, Manh Luong, Tin Duy Vo, Hung Hai Bui, Dinh Q. Phung, Dat Quoc Nguyen:
A Vietnamese-English Neural Machine Translation System. INTERSPEECH 2022: 5543-5544 - [c215]Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung:
MED-TEX: Transfer and Explain Knowledge with Less Data from Pretrained Medical Imaging Models. ISBI 2022: 1-4 - [c214]Tin Duy Vo, Manh Luong, Duong Minh Le, Hieu Tran, Nhan Do, Tuan-Duy H. Nguyen, Thien Nguyen, Hung Bui, Dat Quoc Nguyen, Dinh Q. Phung:
Vietnamese Speech-based Question Answering over Car Manuals. IUI Companion 2022: 117-119 - [c213]Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung:
Stochastic Multiple Target Sampling Gradient Descent. NeurIPS 2022 - [c212]Chuanxia Zheng, Tung-Long Vuong, Jianfei Cai, Dinh Phung:
MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. NeurIPS 2022 - [c211]Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, Dinh Q. Phung:
VulRepair: a T5-based automated software vulnerability repair. ESEC/SIGSOFT FSE 2022: 935-947 - [c210]Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung:
Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. UAI 2022: 1519-1529 - [c209]Thuy-Trang Vu, Shahram Khadivi, Xuanli He, Dinh Phung, Gholamreza Haffari:
Can Domains Be Transferred across Languages in Multi-Domain Multilingual Neural Machine Translation? WMT 2022: 381-396 - [c208]Dai Quoc Nguyen, Vinh Tong, Dinh Q. Phung, Dat Quoc Nguyen:
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction. WSDM 2022: 1589-1592 - [c207]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Q. Phung:
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. WWW (Companion Volume) 2022: 189-192 - [c206]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Universal Graph Transformer Self-Attention Networks. WWW (Companion Volume) 2022: 193-196 - [i96]Tam Le, Truyen Nguyen, Dinh Q. Phung, Viet Anh Nguyen:
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. CoRR abs/2202.10723 (2022) - [i95]Tuan Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung:
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR abs/2202.13437 (2022) - [i94]Hoang Phan, Trung Le, Trung Phung, Tuan Anh Bui, Nhat Ho, Dinh Q. Phung:
Global-Local Regularization Via Distributional Robustness. CoRR abs/2203.00553 (2022) - [i93]Chuanxia Zheng, Guoxian Song, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung, Linjie Luo:
High-Quality Pluralistic Image Completion via Code Shared VQGAN. CoRR abs/2204.01931 (2022) - [i92]Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung:
Stochastic Multiple Target Sampling Gradient Descent. CoRR abs/2206.01934 (2022) - [i91]Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Q. Phung:
An Additive Instance-Wise Approach to Multi-class Model Interpretation. CoRR abs/2207.03113 (2022) - [i90]Chuanxia Zheng, Long Tung Vuong, Jianfei Cai, Dinh Q. Phung:
MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. CoRR abs/2209.09002 (2022) - [i89]Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Hung Nguyen, Dinh Q. Phung:
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle. CoRR abs/2209.10406 (2022) - [i88]Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Hung Nguyen, Seyit Camtepe, Paul Quirk, Dinh Q. Phung:
An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability. CoRR abs/2209.10414 (2022) - [i87]Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin Bonilla, Gholamreza Haffari, Dinh Q. Phung:
Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. CoRR abs/2209.13446 (2022) - [i86]Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong, Thanh-Toan Do, Quan Hung Tran, Dinh Q. Phung, Trung Le:
Vision Transformer Visualization: What Neurons Tell and How Neurons Behave? CoRR abs/2210.07646 (2022) - [i85]Thuy-Trang Vu, Shahram Khadivi, Xuanli He, Dinh Q. Phung, Gholamreza Haffari:
Can Domains Be Transferred Across Languages in Multi-Domain Multilingual Neural Machine Translation? CoRR abs/2210.11628 (2022) - [i84]Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Q. Phung, Trung Le:
Improving Multi-task Learning via Seeking Task-based Flat Regions. CoRR abs/2211.13723 (2022) - [i83]Quyen Tran, Hoang Phan, Khoat Than, Dinh Q. Phung, Trung Le:
Continual Learning with Optimal Transport based Mixture Model. CoRR abs/2211.16780 (2022) - [i82]Ngoc N. Tran, Anh Tuan Bui, Dinh Q. Phung, Trung Le:
Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance. CoRR abs/2212.03069 (2022) - 2021
- [j58]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. 22: 145:1-145:43 (2021) - [c205]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. AAAI 2021: 6831-6839 - [c204]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Quaternion Graph Neural Networks. ACML 2021: 236-251 - [c203]Thuy-Trang Vu, Xuanli He, Dinh Q. Phung, Gholamreza Haffari:
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection. EMNLP (1) 2021: 3335-3346 - [c202]Van-Anh Nguyen, Tuan Nguyen, Trung Le, Quan Hung Tran, Dinh Phung:
STEM: An approach to Multi-source Domain Adaptation with Guarantees. ICCV 2021: 9332-9343 - [c201]He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine:
Neural Topic Model via Optimal Transport. ICLR 2021 - [c200]Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung:
LAMDA: Label Matching Deep Domain Adaptation. ICML 2021: 6043-6054 - [c199]Tuan Nguyen, Trung Le, Nhan Dam, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung:
TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport. IJCAI 2021: 2862-2868 - [c198]Viet Huynh, Dinh Q. Phung, He Zhao:
Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI 2021: 4450-4457 - [c197]He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine:
Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI 2021: 4713-4720 - [c196]Van Nguyen, Trung Le, Olivier Y. de Vel, Paul Montague, John Grundy, Dinh Phung:
Information-theoretic Source Code Vulnerability Highlighting. IJCNN 2021: 1-8 - [c195]Manh-Ha Bui, Toan Tran, Anh Tran, Dinh Q. Phung:
Exploiting Domain-Specific Features to Enhance Domain Generalization. NeurIPS 2021: 21189-21201 - [c194]Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. NeurIPS 2021: 27720-27733 - [c193]Tuan Nguyen, Trung Le, He Zhao, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung:
Most: multi-source domain adaptation via optimal transport for student-teacher learning. UAI 2021: 225-235 - [i81]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung:
Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning. CoRR abs/2101.10027 (2021) - [i80]Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le:
BoMb-OT: On Batch of Mini-batches Optimal Transport. CoRR abs/2102.05912 (2021) - [i79]He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine:
Topic Modelling Meets Deep Neural Networks: A Survey. CoRR abs/2103.00498 (2021) - [i78]Dai Quoc Nguyen, Vinh Tong, Dinh Phung, Dat Quoc Nguyen:
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction. CoRR abs/2104.07396 (2021) - [i77]Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung:
Improved and Efficient Text Adversarial Attacks using Target Information. CoRR abs/2104.13484 (2021) - [i76]Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung:
Text Generation with Deep Variational GAN. CoRR abs/2104.13488 (2021) - [i75]Son Duy Dao, Ethan Zhao, Dinh Phung, Jianfei Cai:
Multi-Label Image Classification with Contrastive Learning. CoRR abs/2107.11626 (2021) - [i74]Jing Liu, Bohan Zhuang, Mingkui Tan, Xu Liu, Dinh Phung, Yuanqing Li, Jianfei Cai:
Elastic Architecture Search for Diverse Tasks with Different Resources. CoRR abs/2108.01224 (2021) - [i73]Thuy-Trang Vu, Xuanli He, Dinh Q. Phung, Gholamreza Haffari:
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection. CoRR abs/2109.04292 (2021) - [i72]Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Q. Phung:
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection. CoRR abs/2110.07317 (2021) - [i71]Manh-Ha Bui, Toan Tran, Anh Tuan Tran, Dinh Phung:
Exploiting Domain-Specific Features to Enhance Domain Generalization. CoRR abs/2110.09410 (2021) - [i70]Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung:
On Label Shift in Domain Adaptation via Wasserstein Distance. CoRR abs/2110.15520 (2021) - [i69]Dang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho:
Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment. CoRR abs/2110.15538 (2021) - [i68]Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. CoRR abs/2111.13822 (2021) - [i67]Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen:
Two-view Graph Neural Networks for Knowledge Graph Completion. CoRR abs/2112.09231 (2021) - 2020
- [j57]Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Hung Nguyen, Duc Thanh Nguyen, John Yearwood, Dinh Quoc Phung, Svetha Venkatesh, Helen Christensen:
Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices. Future Gener. Comput. Syst. 110: 620-628 (2020) - [j56]Wenhe Liu, Xiaojun Chang, Ling Chen, Dinh Phung, Xiaoqin Zhang, Yi Yang, Alexander G. Hauptmann:
Pair-based Uncertainty and Diversity Promoting Early Active Learning for Person Re-identification. ACM Trans. Intell. Syst. Technol. 11(2): 21:1-21:15 (2020) - [c192]Dai Quoc Nguyen, Tuan Nguyen, Dinh Phung:
A Relational Memory-based Embedding Model for Triple Classification and Search Personalization. ACL 2020: 3429-3435 - [c191]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou:
Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS 2020: 1684-1694 - [c190]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung:
A Capsule Network-based Model for Learning Node Embeddings. CIKM 2020: 3313-3316 - [c189]Quan Hung Tran, Nhan Dam, Tuan Manh Lai, Franck Dernoncourt, Trung Le, Nham Le, Dinh Phung:
Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering. COLING 2020: 5205-5210 - [c188]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Q. Phung:
Improving Adversarial Robustness by Enforcing Local and Global Compactness. ECCV (27) 2020: 209-223 - [c187]Thuy-Trang Vu, Dinh Phung, Gholamreza Haffari:
Effective Unsupervised Domain Adaptation with Adversarially Trained Language Models. EMNLP (1) 2020: 6163-6173 - [c186]Quan Hoang, Trung Le, Dinh Phung:
Parameterized Rate-Distortion Stochastic Encoder. ICML 2020: 4293-4303 - [c185]Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung:
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. ICPR 2020: 8922-8928 - [c184]Nhan Dam, Trung Le, Viet Huynh, Dinh Phung:
Stein Variational Gradient Descent with Variance Reduction. IJCNN 2020: 1-8 - [c183]Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung:
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation. IJCNN 2020: 1-8 - [c182]Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier Y. de Vel, Paul Montague, Dinh Phung:
Code Pointer Network for Binary Function Scope Identification. IJCNN 2020: 1-7 - [c181]Viet Huynh, He Zhao, Dinh Phung:
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling. NeurIPS 2020 - [c180]Tuan Nguyen, Trung Le, Khanh Nguyen, Olivier Y. de Vel, Paul Montague, John C. Grundy, Dinh Phung:
Deep Cost-Sensitive Kernel Machine for Binary Software Vulnerability Detection. PAKDD (2) 2020: 164-177 - [c179]Van Nguyen, Trung Le, Olivier Y. de Vel, Paul Montague, John C. Grundy, Dinh Phung:
Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection. PAKDD (1) 2020: 699-711 - [c178]Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier Y. de Vel, Paul Montague, John C. Grundy, Dinh Phung:
Code Action Network for Binary Function Scope Identification. PAKDD (1) 2020: 712-725 - [c177]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-attention Network Based Node Embedding Model. ECML/PKDD (3) 2020: 364-377 - [i66]Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung:
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation. CoRR abs/2004.07534 (2020) - [i65]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-Attention Network based Node Embedding Model. CoRR abs/2006.12100 (2020) - [i64]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung:
Improving Adversarial Robustness by Enforcing Local and Global Compactness. CoRR abs/2007.05123 (2020) - [i63]Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung:
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models. CoRR abs/2008.02593 (2020) - [i62]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
Quaternion Graph Neural Networks. CoRR abs/2008.05089 (2020) - [i61]He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine:
Neural Sinkhorn Topic Model. CoRR abs/2008.13537 (2020) - [i60]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung:
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. CoRR abs/2009.09612 (2020) - [i59]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Phung:
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. CoRR abs/2009.12517 (2020) - [i58]Thuy-Trang Vu, Dinh Phung, Gholamreza Haffari:
Effective Unsupervised Domain Adaptation with Adversarially Trained Language Models. CoRR abs/2010.01739 (2020) - [i57]He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images. CoRR abs/2010.06131 (2020) - [i56]Mahmoud Hossam, Trung Le,