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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
- 2024
[j68]Michael Fu, Chakkrit Tantithamthavorn
, Trung Le, Yuki Kume, Van Nguyen, Dinh Q. Phung, John C. Grundy:
AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities. Empir. Softw. Eng. 29(1): 4 (2024)- [j67]Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai:
Class Enhancement Losses With Pseudo Labels for Open-Vocabulary Semantic Segmentation. IEEE Trans. Multim. 26: 8442-8453 (2024) - [j66]Michael Fu, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung, Trung Le:
Vision Transformer Inspired Automated Vulnerability Repair. ACM Trans. Softw. Eng. Methodol. 33(3): 78:1-78:29 (2024) - [j65]Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Dinh Q. Phung:
Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection. ACM Trans. Softw. Eng. Methodol. 33(6): 162 (2024) - [c244]Thi Nguyen, Linhao Luo, Fatemeh Shiri, Dinh Phung, Yuan-Fang Li, Thuy-Trang Vu, Gholamreza Haffari:
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs. ACL (Findings) 2024: 2862-2883 - [c243]Manh Luong, Khai Nguyen, Nhat Ho, Reza Haf, Dinh Phung, Lizhen Qu:
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. ICLR 2024 - [c242]Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung:
Optimal Transport for Structure Learning Under Missing Data. ICML 2024 - [c241]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung:
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport. ICML 2024 - [c240]Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do:
Frequency Attention for Knowledge Distillation. WACV 2024: 2266-2275 - [i130]Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung:
A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation. CoRR abs/2401.15952 (2024) - [i129]Minh-Vuong Nguyen, Linhao Luo, Fatemeh Shiri, Dinh Phung, Yuan-Fang Li, Thuy-Trang Vu, Gholamreza Haffari:
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs. CoRR abs/2402.11199 (2024) - [i128]Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung:
Optimal Transport for Structure Learning Under Missing Data. CoRR abs/2402.15255 (2024) - [i127]Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do:
Frequency Attention for Knowledge Distillation. CoRR abs/2403.05894 (2024) - [i126]Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung:
Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts. CoRR abs/2403.12326 (2024) - [i125]Anh Bui, Vy Vo, Tung Pham, Dinh Q. Phung, Trung Le:
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers. CoRR abs/2403.13204 (2024) - [i124]Minh-Tuan Tran, Trung Le, Xuan-May Thi Le, Mehrtash Harandi, Dinh Phung:
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning. CoRR abs/2403.14101 (2024) - [i123]Cheng Zhang, Qianyi Wu, Camilo Cruz Gambardella, Xiaoshui Huang, Dinh Q. Phung, Wanli Ouyang, Jianfei Cai:
Taming Stable Diffusion for Text to 360{\deg} Panorama Image Generation. CoRR abs/2404.07949 (2024) - [i122]Manh Luong, Khai Nguyen, Nhat Ho, Reza Haf, Dinh Q. Phung, Lizhen Qu:
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. CoRR abs/2405.10084 (2024) - [i121]Shangyu Chen, Zizheng Pan, Jianfei Cai, Dinh Q. Phung:
PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction. CoRR abs/2406.05641 (2024) - [i120]Van-Anh Nguyen, Quyen Tran, Tuan Truong, Thanh-Toan Do, Dinh Quoc Phung, Trung Le:
Agnostic Sharpness-Aware Minimization. CoRR abs/2406.07107 (2024) - [i119]Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du:
LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. CoRR abs/2406.09008 (2024) - [i118]Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do:
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. CoRR abs/2407.02721 (2024) - [i117]Cuong Pham, Hoang Anh Dung, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do:
MetaAug: Meta-Data Augmentation for Post-Training Quantization. CoRR abs/2407.14726 (2024) - 2023
- [j64]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) - [j63]Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai:
Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing 555: 126605 (2023) - [j62]Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung:
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. Trans. Mach. Learn. Res. 2023 (2023) - [j61]Michael Fu, Van Nguyen, Chakkrit Kla Tantithamthavorn, Trung Le, Dinh Q. Phung:
VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types. IEEE Trans. Software Eng. 49(10): 4550-4565 (2023) - [c239]Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung:
Global-Local Regularization Via Distributional Robustness. AISTATS 2023: 7644-7664 - [c238]Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung, Reza Haf:
Systematic Assessment of Factual Knowledge in Large Language Models. EMNLP (Findings) 2023: 13272-13286 - [c237]Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen:
Two-View Graph Neural Networks for Knowledge Graph Completion. ESWC 2023: 262-278 - [c236]Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho:
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks. ICASSP 2023: 1-5 - [c235]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 - [c234]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 - [c233]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 - [c232]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 - [c231]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 - [c230]Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung:
Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation. MICCAI (1) 2023: 183-194 - [c229]Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung:
Optimal Transport Model Distributional Robustness. NeurIPS 2023 - [c228]Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le:
Flat Seeking Bayesian Neural Networks. NeurIPS 2023 - [c227]Van Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do:
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. NeurIPS 2023 - [c226]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung:
Adversarial local distribution regularization for knowledge distillation. WACV 2023: 4670-4679 - [i116]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) - [i115]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) - [i114]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) - [i113]Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Q. Phung:
Hyperbolic Geometry in Computer Vision: A Survey. CoRR abs/2304.10764 (2023) - [i112]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) - [i111]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) - [i110]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) - [i109]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Q. Phung:
Learning Directed Graphical Models with Optimal Transport. CoRR abs/2305.15927 (2023) - [i108]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) - [i107]Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung:
Optimal Transport Model Distributional Robustness. CoRR abs/2306.04178 (2023) - [i106]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) - [i105]Xiaohao Yang, He Zhao, Dinh Phung, Lan Du:
Towards Generalising Neural Topical Representations. CoRR abs/2307.12564 (2023) - [i104]Tuan Truong, Hoang-Phi Nguyen, Tung Pham, Minh-Tuan Tran, Mehrtash Harandi, Dinh Phung, Trung Le:
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization. CoRR abs/2309.17215 (2023) - [i103]Minh-Tuan Tran, Trung Le, Xuan-May Thi Le, Mehrtash Harandi, Quan Hung Tran, Dinh Q. Phung:
Unleash Data Generation for Efficient and Effective Data-free Knowledge Distillation. CoRR abs/2310.00258 (2023) - [i102]Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung:
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation. CoRR abs/2310.01176 (2023) - [i101]Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung, Gholamreza Haffari:
Systematic Assessment of Factual Knowledge in Large Language Models. CoRR abs/2310.11638 (2023) - [i100]Dat Quoc Nguyen, Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, Nhung Nguyen, Thien Huu Nguyen, Dinh Q. Phung, Hung Hai Bui:
PhoGPT: Generative Pre-training for Vietnamese. CoRR abs/2311.02945 (2023) - [i99]Ngoc N. Tran, Lam Tran, Hoang Phan, Anh Tuan Bui, Tung Pham, Toan Tran, Dinh Q. Phung, Trung Le:
Robust Contrastive Learning With Theory Guarantee. CoRR abs/2311.09671 (2023) - [i98]Quyen Tran, Lam Tran, Khoat Than, Toan Tran, Dinh Q. Phung, Trung Le:
KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All. CoRR abs/2311.15414 (2023) - [i97]Khanh Doan, Quyen Tran, Tuan Nguyen, Dinh Q. Phung, Trung Le:
Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay. CoRR abs/2312.06710 (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 V. 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]