Trung Le

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 165

Top Venues

Publications

Michael Fu, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung, Trung Le
Vision Transformer Inspired Automated Vulnerability Repair. ACM Trans. Softw. Eng. Methodol. 33 (3) (2024)
Jing Wu, Trung Le, Munawar Hayat, Mehrtash Harandi
EraseDiff: Erasing Data Influence in Diffusion Models. CoRR (2024)
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 (2024)
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 (2024)
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) (2024)
Hoang Phan, Lam Tran, Quyen Tran, Trung Le
Enhancing Domain Adaptation through Prompt Gradient Alignment. CoRR (2024)
Anh Bui, Vy Vo, Tung Pham, Dinh Q. Phung, Trung Le
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers. CoRR (2024)
Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do
Frequency Attention for Knowledge Distillation. WACV (2024)
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 (2024)
Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung
Optimal Transport for Structure Learning Under Missing Data. CoRR (2024)
Parul Gupta, Tuan Nguyen, Abhinav Dhall, Munawar Hayat, Trung Le, Thanh-Toan Do
DiffAugment: Diffusion based Long-Tailed Visual Relationship Recognition. CoRR (2024)
Tuan-Luc Huynh, Thuy-Trang Vu, Weiqing Wang, Yinwei Wei, Trung Le, Dragan Gasevic, Yuan-Fang Li, Thanh-Toan Do
PromptDSI: Prompt-based Rehearsal-free Instance-wise Incremental Learning for Document Retrieval. CoRR (2024)
Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do
Frequency Attention for Knowledge Distillation. CoRR (2024)
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) (2024)
Minh-Tuan Tran, Trung Le, Xuan-May Thi Le, Mehrtash Harandi, Dinh Phung
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning. CoRR (2024)
Van-Anh Nguyen, Quyen Tran, Tuan Truong, Thanh-Toan Do, Dinh Quoc Phung, Trung Le
Agnostic Sharpness-Aware Minimization. CoRR (2024)
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 (2024)
Benzfica Hanif, Aisyah Larasati, Rudi Nurdiansyah, Trung Le
The Effect of the Number of Hidden Layers on The Performance of Deep Q-Network for Traveling Salesman Problem. Knowl. Eng. Data Sci. 6 (2) (2023)
Alex Davila-Frias, Nita Yodo, Trung Le, Om Prakash Yadav
A deep neural network and Bayesian method based framework for all-terminal network reliability estimation considering degradation. Reliab. Eng. Syst. Saf. 229 (2023)
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 (2023)
Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung
Optimal Transport Model Distributional Robustness. CoRR (2023)
Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
Vector Quantized Wasserstein Auto-Encoder. ICML (2023)
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 (2023)
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)
Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Q. Phung, Trung Le
Sharpness & Shift-Aware Self-Supervised Learning. CoRR (2023)
Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Q. Phung
Hyperbolic Geometry in Computer Vision: A Survey. CoRR (2023)
Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Q. Phung
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities. CoRR (2023)
Trung Le, Zhao Zhang, Zhichun Zhu
Polling-Based Memory Interface. ACM Trans. Design Autom. Electr. Syst. 28 (3) (2023)
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 (2023)
Peiyun Wu, Trung Le, Zhichun Zhu, Zhao Zhang
Redundant Array of Independent Memory Devices. IEEE Comput. Archit. Lett. 22 (2) (2023)
Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung
Optimal Transport Model Distributional Robustness. NeurIPS (2023)
Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le
Flat Seeking Bayesian Neural Networks. NeurIPS (2023)
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)
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 (2023)
Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung
Global-Local Regularization Via Distributional Robustness. AISTATS (2023)
Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
Vector Quantized Wasserstein Auto-Encoder. CoRR (2023)
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 (2023)
Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin Bonilla, Dinh Q. Phung
Learning Directed Graphical Models with Optimal Transport. CoRR (2023)
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 (2023)
Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. NeurIPS (2023)
Michael Fu, Chakkrit Tantithamthavorn, Van Nguyen, Trung Le
ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We? CoRR (2023)
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)
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 (2023)
Soumyadeep Hore, Quoc H. Nguyen, Yulun Xu, Ankit Shah, Nathaniel D. Bastian, Trung Le
Empirical Evaluation of Autoencoder Models for Anomaly Detection in Packet-based NIDS. DSC (2023)
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)
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) (2023)
Michael Fu, Chakkrit Kla Tantithamthavorn, Van Nguyen, Trung Le
ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We? APSEC (2023)
Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. CoRR (2023)
Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung
Adversarial local distribution regularization for knowledge distillation. WACV (2023)
Khanh Doan, Quyen Tran, Tuan Nguyen, Dinh Q. Phung, Trung Le
Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay. CoRR (2023)
Van-Anh Nguyen, Long Tung Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le
Flat Seeking Bayesian Neural Networks. CoRR (2023)
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)
Jingyuan Li, Leo Scholl, Trung Le, Pavithra Rajeswaran, Amy Orsborn, Eli Shlizerman
AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity. NeurIPS (2023)
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 (2022)
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 (2022)
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)
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)
Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, Dinh Q. Phung
VulRepair: a T5-based automated software vulnerability repair. ESEC/SIGSOFT FSE (2022)
Thien Pham, Trung Le, Dat Dang, Hung Bui, Hoang Pham, Loi Truong, Mao Nguyen, Thanh Hung Vo, Quan Thanh Tho
ARNS: A Data-Driven Approach for SoH Estimation of Lithium-Ion Battery Using Nested Sequence Models With Considering Relaxation Effect. IEEE Access 10 (2022)
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) (2022)
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 (2022)
Trung Le, Khanh Nguyen, Dinh Q. Phung
Improving kernel online learning with a snapshot memory. Mach. Learn. 111 (3) (2022)
Hoang Phan, Trung Le, Trung Phung, Tuan Anh Bui, Nhat Ho, Dinh Q. Phung
Global-Local Regularization Via Distributional Robustness. CoRR (2022)
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 (2022)
Trung Le, Eli Shlizerman
STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers. NeurIPS (2022)
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 (2022)
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Stochastic Multiple Target Sampling Gradient Descent. CoRR (2022)
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 (2022)
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)
Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR (2022)
Tuan Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR (2022)
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)
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Stochastic Multiple Target Sampling Gradient Descent. NeurIPS (2022)
Quyen Tran, Hoang Phan, Khoat Than, Dinh Q. Phung, Trung Le
Continual Learning with Optimal Transport based Mixture Model. CoRR (2022)
Trung Le, Eli Shlizerman
STNDT: Modeling Neural Population Activity with a Spatiotemporal Transformer. CoRR (2022)
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 (2022)
Ehsan K. Ardestani, Changkyu Kim, Seung Jae Lee, Luoshang Pan, Jens Axboe, Valmiki Rampersad, Banit Agrawal, Fuxun Yu, Ansha Yu, Trung Le, Hector Yuen, Dheevatsa Mudigere, Shishir Juluri, Akshat Nanda, Manoj Wodekar, Krishnakumar Nair, Maxim Naumov, Chris Petersen, Mikhail Smelyanskiy, Vijay Rao
Supporting Massive DLRM Inference through Software Defined Memory. ICDCS (2022)
Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung
Particle-based Adversarial Local Distribution Regularization. AISTATS (2022)
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)
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 (2021)
Van Nguyen, Trung Le, Olivier Y. de Vel, Paul Montague, John Grundy, Dinh Phung
Information-theoretic Source Code Vulnerability Highlighting. IJCNN (2021)
Trung Le, Zhao Zhang, Zhichun Zhu
POMI: Polling-Based Memory Interface for Hybrid Memory System. ICCD (2021)
Trung Le, Ryan Poplin, Fred Bertsch, Andeep Singh Toor, Margaret L. Oh
SyntheticFur dataset for neural rendering. CoRR (2021)
Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le
BoMb-OT: On Batch of Mini-batches Optimal Transport. CoRR (2021)
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 (2021)
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)
Claudio Paoloni, Rupa Basu, Marcel Burhenn, Maruf Hossain, Daniel Huebsch, Viktor Krozer, Trung Le, Rosa Letizia, Ernesto Limiti, François Magne, Marc Marilier, Antonio Ramirez, Jeevan M. Rao, Giacomo Ulisse, Borja Vidal, Hadi Yacob
Toward the first D-band Point to multipoint wireless system field test. EuCNC/6G Summit (2021)
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 (2021)
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
Neural Topic Model via Optimal Transport. ICLR (2021)
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)
Ehsan K. Ardestani, Changkyu Kim, Seung Jae Lee, Luoshang Pan, Valmiki Rampersad, Jens Axboe, Banit Agrawal, Fuxun Yu, Ansha Yu, Trung Le, Hector Yuen, Shishir Juluri, Akshat Nanda, Manoj Wodekar, Dheevatsa Mudigere, Krishnakumar Nair, Maxim Naumov, Chris Peterson, Mikhail Smelyanskiy, Vijay Rao
Supporting Massive DLRM Inference Through Software Defined Memory. CoRR (2021)
Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
Improved and Efficient Text Adversarial Attacks using Target Information. CoRR (2021)
Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung
Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning. CoRR (2021)
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)
Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung
Text Generation with Deep Variational GAN. CoRR (2021)
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
LAMDA: Label Matching Deep Domain Adaptation. ICML (2021)
Van-Anh Nguyen, Tuan Nguyen, Trung Le, Quan Hung Tran, Dinh Phung
STEM: An approach to Multi-source Domain Adaptation with Guarantees. ICCV (2021)
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 (2020)
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)
Nhan Dam, Trung Le, Viet Huynh, Dinh Phung
Stein Variational Gradient Descent with Variance Reduction. IJCNN (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Trung Le