Spectral Flattening Is All Muon Needs: How Orthogonalization Controls Learning Rate and Convergence
Tien-Phat Nguyen, Truong Nguyen, Minh-Phuc Truong, Tuc Nguyen, James Bailey, Trung Le
arXiv preprint arXiv:2605.13079
Publications
Publications
2026
BSO: Safety Alignment Is Density Ratio Matching
Tien-Phat Nguyen, Truong Nguyen, Thin Nguyen, Duy Minh Ho Nguyen, Ngoc-Thanh Dinh, Trung Le
arXiv preprint arXiv:2605.12339
Selective Off-Policy Reference Tuning with Plan Guidance
Duc Anh Le, Tien-Phat Nguyen, Thien Huu Nguyen, Linh Ngo Van, Trung Le
arXiv preprint arXiv:2605.11505
Efficient Test-Time Scaling for LLM-based Time Series Forecasting
Xuan-May Le, Minh-Tuan Tran, Ling Luo, Uwe Aickelin, Dinh Phung, Trung Le
SIGKDD Conference on Knowledge Discovery and Data Mining, 2026
LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models
Minh Chu Xuan, Tien-Phat Nguyen, Linh Ngo Van, Dinh Viet Sang, Nguyen Thi Ngoc Diep, Trung Le
arXiv preprint arXiv:2605.03299
Diverse Image Priors for Black-box Data-free Knowledge Distillation
Tri-Nhan Vo, Dang Nguyen, Trung Le, Kien Do, Sunil Gupta
International Conference on Computer Communication and the Internet (ICCCI 26)
Does a Hybrid Space-Aware Randomized Defense Improve Empirical and Certified Adversarial Robustness?
Joy Dhar, Manish Kumar Pandey, Behzad Bozorgtabar, Trung Le, Lina et al. Yao
International Conference on Machine Learning (ICML 2026)
f-Divergence Self-Play for Tabular Anomaly Detection via Large Language Models
Vuong Hoang Tran, Van Linh Ngo, Dang Nguyen, Thin Nguyen, Phuoc Nguyen, Mehrtash Harandi, Trung Le
International Conference on Machine Learning (ICML 2026)
Causal-aware Anomaly Detection for Tabular Data Focus: Causal AI & Tabular Data
Dang Nguyen, Tu Anh Hoang Nguyen, Thuc Duy Le, Svetha Venkatesh, Trung Le, Sunil Gupta
International Conference on Machine Learning (ICML 2026)
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching
Truong Nguyen, Tien-Phat Nguyen, Linh Ngo Van, Duy Minh Ho Nguyen, Khoa D. Doan, Trung Le
International Conference on Machine Learning (ICML 2026)
HieRD: Hierarchical Relational Distillation for Vision-Language Embedding Models
Vinh Le, Nguyen Hong Dang, Tu Vu, Linh Ngo Van, Duc Anh Nguyen, Trung Le
International Conference on Machine Learning (ICML 2026)
Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models
Cuong Pham, Anh Dung Hoang, Cuong C. Nguyen, Trung Le, Gustavo Carneiro, Thanh-Toan Do
Annual Meeting of the Association for Computational Linguistics (ACL 2026)
RoNE: Robust Neurons Enable Internal Defenses Against Multimodal Jailbreak
Tung Lam Tran, Hoang Phan, Christopher Kanan, Trung Le
Annual Meeting of the Association for Computational Linguistics (ACL 2026)
MemORAI: Memory Organization and Retrieval via Adaptive Graph Intelligence for LLM Conversational Agents
Van Hung Pham, Manh Hieu Nguyen, Tran Tuan Khang Pham, Hai Nam Le, Van Linh Ngo, Thi Ngoc Diep Nguyen, Trung Le
Findings of Annual Meeting of the Association for Computational Linguistics (ACL 2026)
SRA: Span Representation Alignment for Large Language Model Distillation
Quoc Phong Dao, Hoang Son Nguyen, Khanh Chi Pham, Tung Nguyen, Van Linh Ngo, Nguyen. Thi Ngoc Diep, Trung Le
Annual Meeting of the Association for Computational Linguistics (ACL 2026)
TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation
Quoc Phong Dao, Hoang Son Nguyen, Khanh Chi Pham, Van Linh Ngo, Thi Ngoc Diep Nguyen, Thien Huu Nguyen, Trung Le
Annual Meeting of the Association for Computational Linguistics (ACL 2026)
MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation
Khanh Chi Pham, Quoc Phong Dao, Thuat Nguyen, Van Linh Ngo, Trung Le, Thanh Hong Nguyen
Annual Meeting of the Association for Computational Linguistics (ACL 2026)
MIPIC: Matryoshka Representation Learning via Self-Distilled Intra-Relational and Progressive Information Chaining
Gia Huy Phung, Hai An Vu, Minh-Phuc Truong, Thang Duc Tran, Van Linh Ngo, Thanh Hong Nguyen, Trung Le
Findings of Annual Meeting of the Association for Computational Linguistics (ACL 2026)
LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models
Xuan Minh Chu, Tien-Phat Nguyen, Van Linh Ngo, Viet Sang Dinh, Thi Ngoc Diep Nguyen, Trung Le
Annual Meeting of the Association for Computational Linguistics (ACL 2026)
MCW-KD: Multi-Cost Wasserstein Knowledge Distillation for Large Language Models
Hoang Tran Vuong, Tue Le, Quyen Tran, Linh Ngo Van, Trung Le
Proceedings of the AAAI Conference on Artificial Intelligencevol. 40, pp. 33332–33340
pH-Strips for Selective Forgetting: A Blunt but Fast Diagnostic Baseline for Machine Unlearning
Chengyao Qian, Jing Wu, Trung Le, Dinh Phung, Mehrtash Harandi
Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026)
Test-Time Instance-Specific Parameter Composition: A New Paradigm for Adaptive Generative Modeling
Minh-Tuan Tran, Xuan-May Le, Quan Hung Tran, Mehrtash Harandi, Dinh Phung, Trung Le
Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026)
Exemplar-Free Continual Learning for State Space Models
Lee Isaac Ning, Leila Mahmoodi, Trung Le, Mehrtash Harandi
Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026)
An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning
Quyen Tran, Ngoc-Hai Nguyen, Quan Dao, Hoang Phan, Ngo Van-Linh, Khoat Than, Dinh Phung, Dimitris N. Metaxas, Trung Le
Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026)
Efficient Temporal-aware Matryoshka Adaptation for Temporal Information Retrieval
Tuan-Luc Huynh, Weiqing Wang, Trung Le, Thuy-Trang Vu, Dragan Gašević, Yuan-Fang Li, Thanh-Toan Do
arXiv preprint arXiv:2601.05549
Ordering-based Causal Discovery via Generalized Score Matching
Vy Vo, He Zhao, Trung Le, Edwin V Bonilla, Dinh Phung
SIGKDD Conference on Knowledge Discovery and Data Mining, 2026
Align-SAM: Seeking Flatter Minima for Better Cross-Subset Alignment
Van-Anh Nguyen, Mehrtash Harandi, Thanh-Toan Do, Van Linh Ngo, Dinh Phung, Trung Le
International Conference on Representation Learning (ICLR 2026)
Beyond Uniformity: Sample and Frequency Meta Weighting for Post-Training Quantization of Diffusion Models
Cuong Pham, Dung Anh Hoang, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do
International Conference on Representation Learning (ICLR 2026)
Sharpness-Aware Minimization in Logit Space Efficiently Enhances Direct Preference Optimization
Haocheng Luo, Zehang Deng, Thanh-Toan Do, Mehrtash Harandi, Dinh Phung, Trung Le
International Conference on Representation Learning (ICLR 2026)
Gradient-Aligned Calibration for Post-Training Quantization of Diffusion Models
Dung Anh Hoang, Cuong Pham, Trung Le, Jianfei Cai, Thanh-Toan Do
International Conference on Representation Learning (ICLR 2026)
Understanding Collaboration Mechanism In VAE Recommender Systems
Long Tung Vuong, Julien Monteil, Hien Dang, Volodymyr Vaskovych, Trung Le, Vu Nguyen
International Conference on Representation Learning (ICLR 2026)
Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment
Anh Tuan Bui, Thuy-Trang Vu, Trung Le, Junae Kim, Tamas Abraham, Rollin Omari, Amardeep Kaur, Dinh Phung
International Conference on Representation Learning (ICLR 2026)
Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence
Quoc Minh Nguyen, Trung Le, Jing Wu, Anh Tuan Bui, Mehrtash Harandi
International Conference on Representation Learning (ICLR 2026)
Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models
Thanh Vinh Nguyen, Van Dong Ngo, Xuan Minh Chu, Tung Nguyen, Van Linh Ngo, Viet Sang Dinh, Trung Le
Findings of European Chapter of the Association for Computational Linguistics (EACL)
Causal Direct Preference Optimization for Language Model Alignment
Uyen Le, Thin Nguyen, Toan Nguyen, Toan Doan, Trung Le, Bac Le
Findings of European Chapter of the Association for Computational Linguistics (EACL)
DWA-KD: Dual-Space Weighting and Time-Warped Alignment for Cross-Tokenizer Knowledge Distillation
Duc Trung Vu, Khanh Chi Pham, Dat Phi Van, Ngo, Van Linh, Viet Sang Dinh, Trung Le
Findings of European Chapter of the Association for Computational Linguistics (EACL)
CTPD: Cross Tokenizer Preference Distillation
Truong Nguyen, Van-Phi Dat, Ngan Nguyen, Van-Linh Ngo, Trung Le, Hong-Thanh Nguyen
AAAI Conference on Artificial Intelligence (AAAI 2026)
DIET: Machine Unlearning on a Data-Diet
Nilakshan Kunananthaseelan, Jing Wu, Trung Le, Gholamreza Haffari, Mehrtash Harandi
AAAI Conference on Artificial Intelligence (AAAI 2026)
Co-Steer: Cross-Modal Collaborative Steering for Jailbreaking MLLMs
Jingmin Zhu, Rollin Omari, Tamas Abraham, Junae Kim, Amardeep Kaur, Trung Le, Dinh Phung, Qiuhong Ke
European Conference on Computer Vision (ECCV 2026)
Spectral-Aware Analytic Class-Incremental Learning for Long-Tailed Distributions
Quyen Tran, Ngoc-Hai Nguyen, Quan Dao, Zhuowei Li, Nam Le Hai, Trung Le, Dimitris N. Metaxas
European Conference on Computer Vision (ECCV 2026)
2025
XTRA: Cross-Lingual Topic Modeling with Topic and Representation Alignments
Tien Phat Nguyen, Vu Minh Ngo, Tung Nguyen, Linh Van Ngo, Duc Anh Nguyen, Sang Dinh, Trung Le
arXiv e-printspp. arXiv–2510
Sharpness-Guided Group Relative Policy Optimization via Probability Shaping
Tue Le, Linh Ngo Van, Trung Le
arXiv preprint arXiv:2511.00066
Adaptive Layer-Wise Transformations for Post-Training Quantization of Large Language Models
Cuong Pham, Hoang Anh Dung, Cuong C Nguyen, Trung Le, Gustavo Carneiro, Jianfei Cai, Thanh-Toan Do
arXiv preprint arXiv:2511.17809
Cot2align: Cross-chain of thought distillation via optimal transport alignment for language models with different tokenizers
Anh Duc Le, Tu Vu, Nam Le Hai, Nguyen Thi Ngoc Diep, Linh Ngo Van, Trung Le, Thien Huu Nguyen
arXiv preprint arXiv:2502.16806
Token-Level Self-Play with Importance-Aware Guidance for Large Language Models
Tue Le, Hoang Tran Vuong, Quyen Tran, Linh Ngo Van, Mehrtash Harandi, Trung Le
Conference on Neural Information Processing Systems (NeurIPS 2025)
Geometry-Aware Collaborative Multi-Solutions Optimizer for Model Fine-Tuning with Parameter Efficiency
Van-Anh Nguyen, Trung Le, Mehrtash Harandi, Ehsan Abbasnejad, Thanh-Toan Do, Dinh Phung
Conference on Neural Information Processing Systems (NeurIPS 2025)
Unveiling m-Sharpness Through the Structure of Stochastic Gradient Noise
Haocheng Luo, Mehrtash Harandi, Dinh Phung, Trung Le
Conference on Neural Information Processing Systems (NeurIPS 2025)
DeepVulMatch: Learning and Matching Latent Vulnerability Representations for Dual-Granularity Vulnerability Detection
Fu Michael, Nguyen Van, Tantithamthavorn Chakkrit (Kla), Le Trung, Phung Dinh
IEEE Transactions on Reliability
XTRA: Cross-Lingual Topic Modeling with Topic and Representation Alignments
Tien Phat Nguyen, Vu Minh Ngo, Tung Nguyen, Linh Ngo Van, Duc Anh Nguyen, Sang Dinh, Trung Le
Empirical Methods in Natural Language Processing (2025)
EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments
Minh Phuc Truong, Hai An Vu, Tu Vu, Nguyen Thi Ngoc Diep, Linh Ngo Van, Thien Huu Nguyen, Trung Le
Empirical Methods in Natural Language Processing (2025)
MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora
Tuan-Luc Huynh, Thuy-Trang Vu, Weiqing Wang, Trung Le, Dragan Gasevic, Yuan-Fang Li, Thanh-Toan Do
Empirical Methods in Natural Language Processing (2025)
Multi-Surrogate-Objective Optimization for Neural Topic Models
Tue Le, Hoang Tran Vuong, Tung Nguyen, Linh Ngo Van, Sang Dinh, Trung Le, Huu Nguyen, Thien
Empirical Methods in Natural Language Processing (2025)
A Good Teacher Adapts Their Knowledge for Distillation
Chengyao Qian, Trung Le, Mehrtash Harandi
International Conference on Computer Vision (ICCV 2025)
Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective
Hoang Phan, Tung Lam Tran, Quyen Tran, Ngoc Tran, Tuan Truong, Lei Qi, Nhat Ho, Phung Dinh, Trung Le
International Conference on Computer Vision (ICCV 2025)
Mutual-pairing data augmentation for fewshot continual relation extraction
Nguyen Hoang Anh, Quyen Tran, Thanh Xuan Nguyen, Nguyen Thi Ngoc Diep, Linh Ngo Van, Thien Huu Nguyen, Trung Le
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)pp. 4057–4075
DAViT: A domain-adapted vision transformer for automated pneumonia detection and explanation using chest X-ray images
Michael Fu, Chakkrit Tantithamthavorn, Trung Le
IEEE Access
HVQ-VAE: Variational auto-encoder with hyperbolic vector quantization
Shangyu Chen, Pengfei Fang, Mehrtash Harandi, Trung Le, Jianfei Cai, Dinh Phung
Computer Vision and Image Understandingvol. 258, pp. 104392
RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts
Tuan Truong, Chau Nguyen, Huy Nguyen, Minh Le, Trung Le, Nhat Ho
International Conference on Machine Learning (ICML 2025)
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
Tuan Truong, Ngoc-Quan Pham, Quyen Tran, Tan Minh Nguyen, Dinh Phung, Trung Le
International Conference on Machine Learning (ICML 2025)
Improving Generalization with Flat Hilbert Bayesian Inference
Tuan Truong, Quyen Tran, Ngoc-Quan Pham, Dinh Phung, Nhat Ho, Trung Le
International Conference on Machine Learning (ICML 2025)
Optimizing Specific and Shared Parameters for Efficient Parameter Tuning
Van-Anh Nguyen, Thanh-Toan Do, Mehrtash Harandi, Dinh Phung, Trung Le
arXiv preprint arXiv:2504.03450
Hiding and recovering knowledge in text-to-image diffusion models via learnable prompts
Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Phung
ICLR 2025 Workshop on Deep Generative Model in Machine Learning: Theory, Principle and Efficacy
Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation
Long Tung Vuong, Hoang Phan, Vy Vo, Anh Tuan Bui, Thanh-Toan Do, Dinh Phung, Trung Le
Conference on Computer Vision and Pattern Recognition 2025 (CVPR 2025)
Enhancing Dataset Distillation via Non-Critical Region Refinement
Minh-Tuan Tran, Trung Le, Xuan-May Le, Do Toan, Dinh Phung
Conference on Computer Vision and Pattern Recognition 2025 (CVPR 2025)
Erasing Undesirable Influence in Diffusion Models
Jing Wu, Trung Le, Munawar Hayat, Mehrtash Harandi
Conference on Computer Vision and Pattern Recognition 2025 (CVPR 2025)
Why Domain Generalization Fail? A View of Necessity and Sufficiency
Long-Tung Vuong, Vy Vo, Hien Dang, Van-Anh Nguyen, Thanh-Toan Do, Mehrtash Harandi, Trung Le, Dinh Phung
arXiv preprint arXiv:2502.10716
Mutual-pairing Data Augmentation for Fewshot Continual Relation Extraction
Hoang Anh Nguyen, Quyen Tran, Thanh Xuan Nguyen, Nguyen Thi, Ngoc Diep, Ngo Linh, Thien Huu Nguyen, Trung Le
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2025)
Boosting Multiple Views for pretrained-based Continual Learning
Quyen Tran, Tung Lam Tran, Khanh Doan, Toan Tran, Khoat Than, Dinh Phung, Trung Le
International Conference on Learning Representations 2025 (ICLR 2025)
Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
Anh Tuan Bui, Thuy-Trang Vu, Long Tung Vuong, Trung Le, Paul Montague, Tamas Abraham, Junae Kim, Dinh Phung
International Conference on Learning Representations 2025 (ICLR 2025)
Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
Minh Le, Chau Nguyen, Huy Nguyen, Quyen Tran, Trung Le, Nhat Ho
International Conference on Learning Representations 2025 (ICLR 2025)
Improved Training Technique for Latent Consistency Models
Minh Quan Dao, Khanh Doan, Di Liu, Trung Le, Dimitris Metaxas
International Conference on Learning Representationsvol. 2025, pp. 59678–59695
Large-Scale Data-Free Knowledge Distillation for ImageNet via Multi-Resolution Data Generation
Minh-Tuan Tran, Trung Le, Xuan-May Le, Jianfei Cai, Mehrtash Harandi, Dinh Phung
arXiv preprint arXiv:2411.17046
Leveraging Hierarchical Taxonomies in Prompt-based Continual Learning
Quyen Tran, Hoang Phan, Minh Le, Tuan Truong, Dinh Phung, Linh Ngo, Thien Nguyen, Nhat Ho, Trung Le
arXiv preprint arXiv:2410.04327
PromptDSI: Prompt-Based Rehearsal-Free Continual Learning for Document Retrieval
Tuan-Luc Huynh, Thuy-Trang Vu, Weiqing Wang, Yinwei Wei, Trung Le, Dragan Gasevic, Yuan-Fang Li, Thanh-Toan Do
Joint European Conference on Machine Learning and Knowledge Discovery in Databasespp. 383–401
A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation
Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Phung
WWW 2025: Workshop on Optimal Transport for Structured Data Modeling and Generation
2024
Optimal Transport Theory for Machine Learning with Limited and Less Labels
Trung Le, Dinh Phung, He Zhao
article
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
Long Tung Vuong, Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Phung
Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024)
Explicit Eigenvalue Reguralization Improves Sharpness-Aware Minimization
Haocheng Luo, Tuan Truong, Tung Pham, Mehrtash Harandi, Dinh Phung, Trung Le
Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024)
Preserving Generalization of Language models in Few-shot Continual Relation Extraction
Quyen Tran, Nguyen Xuan Thanh, Nguyen Hoang Anh, Le Nam Hai, Trung Le, Linh Van Ngo, Thien Huu Nguyen
Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)
MetaAug: Meta-Data Augmentation for Post-Training Quantization
Cuong Pham, Dung Hoang, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do
European Conference on Computer Vision 2024 (ECCV 2024)
Enhancing Domain Adaptation through Prompt Gradient Alignment
Hoang Phan, Lam Tran, Quyen Tran, Trung Le
Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024)
Agnostic Sharpness-Aware Minimization
Van-Anh Nguyen, Quyen Tran, Tuan Truong, Thanh-Toan Do, Dinh Phung, Trung Le
arXiv preprint arXiv:2406.07107
Sharpness-Aware Data Generation for Zero-shot Quantization
Hoang Anh Dung, Cuong Pham, Trung Le, Jianfei Cai, Thanh-Toan Do
International Conference on Machine Learning (ICML 2024)
Optimal Transport for Structure Learning Under Missing Data
Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung
International Conference on Machine Learning (ICML 2024)
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung
International Conference on Machine Learning (ICML 2024)
Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection
Van Nguyen, Trung Le, Chakkrit (Kla) Tantithamthavorn, John Grundy, Dinh Phung
Transactions on Software Engineering and Methodology
NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation
Tran Minh-Tuan, Trung Le, Xuan-May Le, Mehrtash Harandi, Quan Hung Tran, Dinh Phung
Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024)
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning
Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Dinh Phung
Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024)
DiffAugment: Diffusion Based Long-Tailed Visual Relationship Recognition
Parul Gupta, Tuan Nguyen, Abhinav Dhall, Munawar Hayat, Trung Le, Thanh-Toan Do
European Conference on Computer Visionpp. 36–52
Frequency attention for knowledge distillation
Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do
Proceedings of the IEEE/CVF winter conference on applications of computer visionpp. 2277–2286
2023
Improving prompt-based continual learning with key-query orthogonal projection and prototype-based one-versus-all
Quyen Tran, Tung Lam Tran, Khoat Than, Toan Tran, Dinh Phung, Trung Le
article
Class-prototype conditional diffusion model for continual learning with generative replay
Khanh Doan, Quyen Tran, Tuan Nguyen, Dinh Phung, Trung Le
arXiv preprint arXiv:2312.06710vol. 1
Koppa: Improving prompt-based continual learning with key-query orthogonal projection and prototype-based one-versus-all
Quyen Tran, Hoang Phan, Lam Tran, Khoat Than, Toan Tran, Dinh Phung, Trung Le
arXiv preprint arXiv:2311.15414
Robust Contrastive Learning With Theory Guarantee
Ngoc N Tran, Lam Tran, Hoang Phan, Anh Bui, Tung Pham, Toan Tran, Dinh Phung, Trung Le
arXiv preprint arXiv:2311.09671
Vision Transformer-Inspired Automated Vulnerability Repair
Michael Fu, Van Nguyen, Chakkrit (Kla) Tantithamthavorn, Dinh Phung, Trung Le
ACM Transactions on Software Engineering and Methodology
ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?
Michael Fu, Chakkrit (Kla) Tantithamthavorn, Van Nguyen, Trung Le
Proceedings of 30th Asia-Pacific Software Engineering Conference (APSEC 2023)
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization
Tuan Truong, Hoang-Phi Nguyen, Tung Pham, Minh-Tuan Tran, Mehrtash Harandi, Dinh Phung, Trung Le
arXiv preprint arXiv:2309.17215
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
VulExplainer: A Transformer-based Hierarchical Distillation for Explaining Vulnerability Types
Michael Fu, Chakkrit (Kla) Tantithamthavorn, Van Nguyen, Trung Le, Dinh Phung
IEEE Transactions on Software Engineering
Learning to quantize vulnerability patterns and match to locate statement-level vulnerabilities
Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung
arXiv preprint arXiv:2306.06109
Optimal Transport Model Distributional Robustness
Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Phung
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation
Thanh Nguyen, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Phung
Medical Image Computing and Computer-Assisted Intervention 2023
AIBugHunter: A Practical Tool for Predicting, Classifying and Repairing Software Vulnerabilities
Michael Fu, Chakkrit (Kla) Tantithamthavorn, Trung Le, Yuki Kume, Van Nguyen, Dinh Phung, John Grundy
Empirical Software Engineering
Sharpness & shift-aware self-supervised learning
Ngoc N Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Phung, Trung Le
arXiv preprint arXiv:2305.10252
Hyperbolic geometry in computer vision: A survey
Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Phung
arXiv preprint arXiv:2304.10764
Flat Seeking Bayesian Neural Networks
Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Phung, Trung Le
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
Vector Quantized Wasserstein Auto-Encoder
Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Phung
Proceedings of the 40th International Conference on Machine Learning (ICML) 2023
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization
Anh Bui, Trung Le, He Zhao, Quan Tran, Paul Montague, Dinh Phung
Transactions on Machine Learning Research (TMLR)
Adversarial local distribution regularization for knowledge distillation
Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Visionpp. 4681–4690
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin Bonilla, Gholamreza Haffari, Dinh Phung
29th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD) 2023
An Additive Instance-Wise Approach to Multi-class Model Interpretation
Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Phung
International Conference on Representation Learning (ICLR) 2023
Global-Local Regularization Via Distributional Robustness
Hoang Phan, Trung Le, Trung Phung, Tuan Anh Bui, Nhat Ho, Dinh Phung
International Conference on Artificial Intelligence and Statistics (AISTATS) 2023
2022
Statement-Level Vulnerability Detection: Learning Vulnerability Patterns Through Information Theory and Contrastive Learning
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, Michael Fu, John Grundy, Hung Nguyen, Seyit Camtepe, Paul Quirk, Dinh Phung
arXiv preprint arXiv:2209.10414
Deep Generative Models for Learning from Multiple High-Dimensional Data Sources
Trung Le
techreport
Multiple Perturbation Attack: Attack Pixelwise Under Different \backslash-norms For Better Adversarial Performance
Ngoc N Tran, Anh Tuan Bui, Dinh Phung, Trung Le
arXiv preprint arXiv:2212.03069
Continual learning with optimal transport based mixture model
Quyen Tran, Hoang Phan, Khoat Than, Dinh Phung, Trung Le
arXiv preprint arXiv:2211.16780
Vision transformer visualization: What neurons tell and how neurons behave?
Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong, Thanh-Toan Do, Quan Hung Tran, Dinh Phung, Trung Le
arXiv preprint arXiv:2210.07646
Stochastic Multiple Target Sampling Gradient Descent
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Thirty-sixth Conference on Neural Information Processing Systems (2022)
On Transportation of Mini-batches: A Hierarchical Approach
Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho
Proceedings of the 39th International Conference on Machine Learningvol. 162, pp. 16622–16655
Cycle Class Consistency with Distributional Optimal Transport and Knowledge Distillation for Unsupervised Domain Adaptation
Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Phung
In the Proceedings of theUncertainty in Artificial Intelligence (UAI) 2022
VulRepair: A T5-Based Automated Software Vulnerability Repair
Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, Dinh Phung
In Proceedings of the Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) (2022)
Invertible residual network with regularization for effective volumetric segmentation
Kashu Yamazaki, Vidhiwar Singh Rathour, T Hoang Ngan Le
Medical Imaging 2021: Image Processingvol. 11596, pp. 269–275
Particle-based Adversarial Local Distribution Regularization
Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung
Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) 2022
On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds
Trung Le, Anh Tuan Bui, Tue Le, He Zhao, Paul Montague, Quan Hung Tran, Phung Dinh
Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Phung
International on Learning Representation (ICLR) 2022
Cross project software vulnerability detection via domain adaptation and max-margin principle
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John Grundy, Hung Nguyen, Dinh Phung
arXiv preprint arXiv:2209.10406
Improving kernel online learning with a snapshot memory
Trung Le, Khanh Nguyen, Dinh Phung
Machine Learningvol. 111, pp. 997–1018
Regvd: Revisiting graph neural networks for vulnerability detection
Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Phung
Proceedings of the ACM/IEEE 44th international conference on software engineering: Companion proceedingspp. 178–182
2021
Roughness index and roughness distance for benchmarking medical segmentation
Vidhiwar Singh Rathour, Kashu Yamakazi, T Le
arXiv preprint arXiv:2103.12350
Offset curves loss for imbalanced problem in medical segmentation
Ngan Le, Trung Le, Kashu Yamazaki, Toan Bui, Khoa Luu, Marios Savides
2020 25th International Conference on Pattern Recognition (ICPR)pp. 9189–9195
On label shift in domain adaptation via wasserstein distance
Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Phung
arXiv preprint arXiv:2110.15520
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
Quoc Trung Phung, Trung Le, Long Tung Vuong, Toan Tran, Tuan Anh Tran, Hung Bui, Dinh Phung
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021)
Stem: An approach to multi-source domain adaptation with guarantees
Van-Anh Nguyen, Tuan Nguyen, Trung Le, Quan Hung Tran, Dinh Phung
Proceedings of the IEEE/CVF International Conference on Computer Visionpp. 9352–9363
Information-theoretic source code vulnerability highlighting
Van Nguyen, Trung Le, Olivier De Vel, Paul Montague, John Grundy, Dinh Phung
2021 International Joint Conference on Neural Networks (IJCNN)pp. 1–8
Tidot: A teacher imitation learning approach for domain adaptation with optimal transport
Tuan Nguyen, Trung Le, Nhan Dam, Quan Hung Tran, Truyen Nguyen, Dinh Phung
International Joint Conference on Artificial Intelligence 2021pp. 2862–2868
Most: Multi-source domain adaptation via optimal transport for student-teacher learning
Tuan Nguyen, Trung Le, He Zhao, Quan Hung Tran, Truyen Nguyen, Dinh Phung
Uncertainty in Artificial Intelligencepp. 225–235
Lamda: Label matching deep domain adaptation
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
Proceedings of the 38th International Conference on Machine Learning (ICML) 2021pp. 6043–6054
Understanding and achieving efficient robustness with adversarial supervised contrastive learning
Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung
arXiv preprint arXiv:2101.10027
Improved and Efficient Text Adversarial Attacks using Target Information
Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
arXiv preprint arXiv:2104.13484
IMPROVING TEXT BLACK-BOX ADVERSARIAL ATTACKS USING TARGET MODEL INFORMATION
Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
Workshop on Robust and Reliable Machine Learning in the Real World (RobustML)
Explain2Attack: Text adversarial attacks via cross-domain interpretability
Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung
2020 25th international conference on pattern recognition (ICPR)pp. 8922–8928
Improving ensemble robustness by collaboratively promoting and demoting adversarial robustness
Anh Tuan Bui, Trung Le, He Zhao, Paul Montague, Olivier deVel, Tamas Abraham, Dinh Phung
Proceedings of the AAAI Conference on Artificial Intelligencevol. 35, pp. 6831–6839
Text generation with deep variational GAN
Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung
arXiv preprint arXiv:2104.13488
2020
Learning to Attack with Fewer Pixels: A Probabilistic Post-hoc Framework for Refining Arbitrary Dense Adversarial Attacks
He Zhao, Thanh Nguyen, Trung Le, Paul Montague, Olivier De Vel, Tamas Abraham, Dinh Phung
arXiv preprint arXiv:2010.06131
The impact of capital structure on the performance of construction companies: A study from Vietnam stock exchanges
T Vu, T Le, T Nguyen
Accountingvol. 6, pp. 169–176
The effect of corporate social responsibility on performance in Nam Dinh seafood enterprises
T Vu, H Tran, T Le, H Nguyen
Management Science Lettersvol. 10, pp. 175–182
Factors affecting teachers’ behavioral intention of using information technology in lecturing-economic universities
Thi Bich Thu Pham, Lan Anh Dang, Thi Minh Hue Le, Thi Hong Le
Management Science Lettersvol. 10, pp. 2665–2672
Robust Variational Learning for Multiclass Kernel Models with Stein Refinement
Khanh Nguyen, Trung Le, Tu Nguyen, Geoffrey Webb, Dinh Phung
IEEE Transactions on Knowledge and Data Engineering
Parameterized rate-distortion stochastic encoder
Quan Hoang, Trung Le, Dinh Phung
International Conference on Machine Learningpp. 4293–4303
Explain by evidence: An explainable memory-based neural network for question answering
Quan Tran, Nhan Dam, Tuan Lai, Franck Dernoncourt, Trung Le, Nham Le, Dinh Phung
Proceedings of the 28th International Conference on Computational Linguistics (2020)
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images.
He Zhao, Trung Le, Paul Montague, Olivier Y de Vel, Tamas Abraham, Dinh Phung
CoRR
Stein variational gradient descent with variance reduction
Nhan Dam, Trung Le, Viet Huynh, Dinh Phung
2020 International Joint Conference on Neural Networks (IJCNN)pp. 1–8
Neural Sinkhorn Topic Model.
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L Buntine
International Conference on Representation Learning (ICLR) 2020
Dual-component deep domain adaptation: A new approach for cross project software vulnerability detection
Van Nguyen, Trung Le, Olivier De Vel, Paul Montague, John Grundy, Dinh Phung
Pacific-Asia Conference on Knowledge Discovery and Data Miningpp. 699–711
Deep cost-sensitive kernel machine for binary software vulnerability detection
Tuan Nguyen, Trung Le, Khanh Nguyen, Olivier de Vel, Paul Montague, John Grundy, Dinh Phung
Pacific-Asia conference on knowledge discovery and data miningpp. 164–177
OptiGAN: Generative adversarial networks for goal optimized sequence generation
Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung
2020 International Joint Conference on Neural Networks (IJCNN)pp. 1–8
Improving adversarial robustness by enforcing local and global compactness
Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier deVel, Tamas Abraham, Dinh Phung
European Conference on Computer Visionpp. 209–223
Code action network for binary function scope identification
Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier de Vel, Paul Montague, John Grundy, Dinh Phung
Pacific-Asia Conference on Knowledge Discovery and Data Miningpp. 712–725
2019
Perturbations are not enough: Generating adversarial examples with spatial distortions
He Zhao, Trung Le, Paul Montague, Olivier De Vel, Tamas Abraham, Dinh Phung
arXiv preprint arXiv:1910.01329
Deep Domain Adaptation for Vulnerable Code Function Identification
Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier DeVel, Paul Montague, Lizhen Qu, Dinh Phung
Int. Joint Conf. on Neural Networks (IJCNN) 2019
Three-Player Wasserstein GAN via Amortised Duality
Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, DInh Phung
International Joint Conference on Artificial Intelligence 2019
Learning Generative Adversarial Networks from Multiple Data Sources
Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, DInh Phung
International Joint Conference on Artificial Intelligence 2019
When can neural networks learn connected decision regions?
Trung Le, Dinh Phung
arXiv preprint arXiv:1901.08710
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection
Tue Le, Tuan Nguyen, Trung Le, Paul Montague, Olivier De Vel, Lizhen Qu, Dinh Phung
In International Conference on Learning Representations (ICLR) 2019
2018
Development and face validation of a Virtual Reality Epley Maneuver System (VREMS) for home Epley treatment of benign paroxysmal positional vertigo: A randomized, controlled trial
Reza Tabanfar, Harley HL Chan, Vincent Lin, Trung Le, Jonathan C Irish
American journal of otolaryngologyvol. 39, pp. 184–191
Bayesian multi-hyperplane machine for pattern recognition
Khanh Nguyen, Trung Le, Tu Nguyen Dinh, Dinh Phung
2018 24th International Conference on Pattern Recognition (ICPR)pp. 609–614
Clustering Induced Kernel Learning
Khanh Nguyen, Trung Le, Tu Nguyen, Dinh Phung
In Asian Conference on Machine Learning
Batch Normalized Deep Boltzmann Machines
Hung Vu, Tu Nguyen, Trung Le, Luo Wei, Dinh Phung
In Asian Conference on Machine Learning
Robust Anomaly Detection in Videos using Multilevel Representations
Hung Vu, Tu Nguyen, Trung Le, Luo Wei, Dinh Phung
In 33rd AAAI Conference on Artificial Intelligence (AAAI 2019)
Jointly predicting affective and mental health scores using deep neural networks of visual cues on the web
Hung Nguyen, Van Nguyen, Thin Nguyen, Mark E Larsen, Bridianne O’Dea, Duc Thanh Nguyen, Trung Le, Dinh Phung, Svetha Venkatesh, Helen Christensen
International Conference on Web Information Systems Engineeringpp. 100–110
GoGP: Scalable Geometric-based Gaussian Process for Online Regression
Trung Le, Khanh Nguyen, Vu Nguyen, Tu Nguyen, Dinh Phung
Knowledge and Information Systems(KAIS) journal
Geometric Enclosing Networks
Trung Le, Hung Vu, Tu Nguyen, Dinh Phung
In Proc. of International Joint Conference on Artificial Intelligence (IJCAI)
Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data
Khanh Nguyen, Trung Le, Tu Nguyen, Dinh Phung, Geoffrey I. Webb
In Proc. of the 24th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD)
MGAN: Training Generative Adversarial Nets with Multiple Generators
Hoang Quan, Nguyen Tu Dinh, Le Trung, Phung Dinh
In International Conference on Learning Representation (ICLR) 2018
2017
Electrophysiological modeling in generalized epilepsy using surface EEG and anatomical brain structures
Q Tran, T Le, CH Le, T Vo Van
International Conference on the Development of Biomedical Engineering in Vietnampp. 699–704
Time series forecasting for healthcare diagnosis and prognostics with the focus on cardiovascular diseases
C Bui, N Pham, Anh Vo, A Tran, A Nguyen, Trung Le
International conference on the development of biomedical engineering in Vietnampp. 809–818
Validation of Wireless Wearable Electrocardiogram System for Real-Time Ambulatory Cardiac Monitoring
Huy Cu, Tuan Nguyen, Tam Nguyen, Trung Le, Toi Vo Van
International Conference on the Development of Biomedical Engineering in Vietnampp. 771–777
Medicine and Surgery
Reza Tabanfar, Harley HL Chan, Vincent Lin, Trung Le, Jonathan C Irish
article
KGAN: how to break the minimax game in GAN
Trung Le, Tu Dinh Nguyen, Dinh Phung
arXiv preprint arXiv:1711.01744
Scalable support vector clustering using budget
Tung Pham, Trung Le, Hang Dang
arXiv preprint arXiv:1709.06444
Analogical-based Bayesian Optimization
Trung Le, Khanh Nguyen, Tu Dinh Nguyen, Dinh Phung
arXiv preprint arXiv:1709.06390
Dual Discriminator Generative Adversarial Nets
Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Phung
In Advances in Neural Information Processing (NIPS) 2017
GoGP: Fast Online Regression with Gaussian Processes
Trung Le, Khanh Nguyen, Vu Nguyen, Nguyen Tu Dinh, Dinh Phung
In International Conference on Data Mining (ICDM 17)
Supervised Restricted Boltzmann Machines
Tu Dinh Nguyen, Dinh Phung, Viet Huynh, Trung Le
In 33rd Conference on Uncertainty in Artificial Intelligence (UAI)
Approximation Vector Machines for Large-scale Online Learning
Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Phung
Journal of Machine Learning Research (JMLR)
Discriminative Bayesian Nonparametric Clustering
Vu Nguyen, Dinh Phung, Trung Le, Svetha Venkatesh, Hung Bui
In Proc. of International Joint Conference on Artificial Intelligence (IJCAI)
Large-scale Online Kernel Learning with Random Feature Reparameterization
Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Phung
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI)
2016
Graph-based Kernel Machine for Scalable Semi-supervised Learning
Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Phung
arXiv preprint arXiv:1606.06793
Scalable Semi-supervised Learning with Graph-based Kernel Machine
Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Phung
arXiv preprint arXiv:1606.06793
One-pass Logistic Regression for Label-drift and Large-scale Classification on Distributed Systems
Vu Nguyen, Tu Dinh Nguyen, Trung Le, Dinh Phung, Svetha Venkatesh
Proceedings of the IEEE International Conference on Data Mining (ICDM) 2016
Dual Space Gradient Descent for Online Learning
Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Phung
In Advances in Neural Information Processing (NIPS) 2016
Distributed Data Augmented Support Vector Machine on Spark
Tu Nguyen, Vu Nguyen, Trung Le, Dinh Phung
Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016)
Multiple Kernel Learning with Data Augmentation
Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Phung
Proceedings of the 8th Asian Conference on Machine Learning (ACML 2016)
Budgeted Semi-supervised Support Vector Machine
Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Phung
32th Conference on Uncertainty in Artificial Intelligence
Mixture of Hyperspheres for Novelty Detection
Duy Nguyen, Vinh Lai, Khanh Nguyen, Trung Le
Vietnam Journal of Computer Science
Fast Kernel-based Method for Anomaly Detection
Anh Le, Trung Le, Khanh Nguyen, Van Nguyen, Thai Hoang Le, Dat Tran
International Joint Conference on Neural Networks
Fuzzy Kernel Stochastic Gradient Descent Machines
Tuan Nguyen, Phuong Duong, Trung Le, Anh Le, Viet Ngo, Dat Tran, Wanli Ma
IJCNN
Fast Support Vector Clustering
Tung Pham, Hang Dang, Trung Le, Thai Hoang Le
Vietnam Journal of Computer Science (VJCS)
Nonparametric Budgeted Stochastic Gradient Descent
Trung Le, Vu Nguyen, Dinh-Tu Nguyen, Dinh Phung
The 19th International Conference on Artificial Intelligence and Statistics (AISTATS)
Sparse Adaptive Multi-Hyperplane Machine
Khanh Nguyen, Trung Le, Vu Nguyen, Dinh Phung
PAKDD
2015
Time series forecasting for nonlinear and non-stationary processes: a review and comparative study
Changqing Cheng, Akkarapol Sa-Ngasoongsong, Omer Beyca, Trung Le, Hui Yang, Zhenyu Kong, Satish TS Bukkapatnam
Iie Transactionsvol. 47, pp. 1053–1071
Large Sample Asymptotic for Nonparametric Mixture Model with Count Data
Vu Nguyen, Dinh Phung, Trung Le, Svetha Venkatesh
NIPS Workshop
Mixture of Support Vector Data Descriptions
Vinh Lai, Duy Nguyen, Khanh Nguyen, Trung Le
NICSpp. 135–140
Stochastic gradient descent support vector clustering
Tung Pham, Hang Dang, Trung Le, Hoang-Thai Le
NICSpp. 88–93
Fast One-Class Support Vector Machine for Novelty Detection
Trung Le, Dinh Phung, Khanh Nguyen, Svetha Venkatesh
PAKDDpp. 189–200
Least square Support Vector Machine for large-scale dataset
Khanh Nguyen, Trung Le, Vinh Lai, Duy Nguyen, Dat Tran, Wanli Ma
IJCNNpp. 1–8
Graph-based semi-supervised Support Vector Data Description for novelty detection
Phuong Duong, Van Nguyen, Mi Dinh, Trung Le, Dat Tran, Wanli Ma
IJCNNpp. 1–6
2014
DECARBURIZATION OF MOLTEN IRON UNDER REDUCED PRESSURE
Anh-Hoa Bui, Thanh-Hai Le, Bao-Trung Nguyen
ASEAN Engineering Journalvol. 3, pp. 55–61
Effects of temperature, doping and anisotropy of energy surfaces on behaviors of plasmons in graphene
S Ta Ho, H Anh Le, T Le, D Chien Nguyen, V Nam Do
Physica E: Low-dimensional Systems and Nanostructuresvol. 58, pp. 101–105
Fuzzy Semi-supervised Large Margin One-Class Support Vector Machine
Trung Le, Van Nguyen, Thien Pham, Mi Dinh, Thai Hoang Le
Some Current Advanced Researches on Information and Computer Science in Vietnampp. 65–78
Robust Support Vector Machine
Trung Le, Dat Tran, Wanli Ma, Thien Pham, Phuong Duong, Minh Nguyen
International Joint Conference on Neural Networks, IJCNN 2014pp. 4137–4144
Kernel-based semi-supervised learning for novelty detection
Van Nguyen, Trung Le, Thien Pham, Mi Dinh, Hoang-Thai Le
IJCNNpp. 4129–4136
Using EEG artifacts for BCI applications
Wanli Ma, Dat Tran, Trung Le, Hong Lin, Shang-Ming Zhou
IJCNNpp. 3628–3635
2013
Expression, purification, crystallization and preliminary X-ray diffraction analysis of a lactococcal bacteriophage small terminase subunit
Bin Ren, Tam M Pham, Regina Surjadi, Christine P Robinson, T Le, PScott Chandry, Thomas S Peat, William J McKinstry
Structural Biology and Crystallization Communicationsvol. 69, pp. 275–279
EEG-Based Person Verification Using Multi-Sphere SVDD and UBM
Phuoc Nguyen, Dat Tran, Trung Le, Xu Huang, Ma Wanli
PAKDDpp. 289–300
Fuzzy entropy semi-supervised support vector data description
Trung Le, Dat Tran, Tien Tran, Khanh Nguyen, Ma Wanli
International Joint Conference on Neural Networkspp. 1–5
Maximal margin learning vector quantisation
Trung Le, Dat Tran, Van Nguyen, Ma Wanli
International Joint Conference on Neural Networkspp. 1–6
Proximity multi-sphere support vector clustering
Trung Le, Dat Tran, Phuoc Nguyen, Wanli Ma, Dharmendra Sharma
Neural Computing and Applicationsvol. 22, pp. 1309–1319
2012
Memetic algorithm for a university course timetabling problem
Khang Nguyen, Tien Lu, Trung Le, Nuong Tran
Informatics in Control, Automation and Robotics: Volume 1pp. 67–71
Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE)
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
WCCI 2012 IEEE World Congress on Computational Intelligencepp. 1956–1960
Multi-modal Approach to Support Vector Machine and Support Vector Data Description
Trung Le
University of Canberra
Multi-sphere support vector data description for brain-computer interface
Phuoc Nguyen, Dat Tran, Trung Le, Tuan Hoang, Dharmendra Sharma
2012 Fourth International Conference on Communications and Electronics (ICCE)pp. 318–321
A unified model for support vector machine and support vector data description
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
International Joint Conference on Neural Networks (IJCNN)pp. 1–8
Time Domain Parameters for Online Feedback fNIRS-Based Brain-Computer Interface Systems
Tuan Hoang, Dat Tran, Khoa Truong, Trung Le, Xu Huang, Dharmendra Sharma, Toi Vo
ICONIPpp. 192–201
Maximal Margin Approach to Kernel Generalised Learning Vector Quantisation for Brain-Computer Interface
Trung Le, Dat Tran, Tuan Hoang, Dharmendra Sharma
ICONIPpp. 191–198
Deterministic Annealing Multi-Sphere Support Vector Data Description
Trung Le, Dat Tran, Wanli Ma, Sharma Dharmendra
International Conference on Neural Information Processingpp. 183–190
2011
Generalised support vector machine for brain-computer interface
Trung Le, Dat Tran, Tuan Hoang, Wanli Ma, Dharmendra Sharma
International Conference on Neural Information Processingpp. 692–700
Multiple Distribution Data Description Learning Algorithm for Novelty Detection
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
PAKDDpp. 256–257
Multi-Sphere Support Vector Clustering
Trung Le, Dat Tran, Phuoc Nguyen, Wanli Ma, Dharmendra Sharma
ICONIPpp. 537–544
A Novel Parameter Refinement Approach to One Class Support Vector Machine
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
International Conference on Neural Information Processingpp. 529–536
2010
Fuzzy support vector machines for age and gender classification
Phuoc Nguyen, Trung Le, Dat Tran, Xu Huang, Dharmendra Sharma
INTERSPEECHpp. 2806–2809
An optimal sphere and two large margins approach for novelty detection
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
IJCNNpp. 1–6
A Theoretical Framework for Multi-sphere Support Vector Data Description
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
ICONIPpp. 132–142
A new support vector machine method for medical image classification
Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma
EUVIPpp. 165–170
Enhancing Performance of SVM-Based Brain-Computer Interface System
Tuan Hoang, Phuoc Nguyen, Trung Le, Dat Tran, Dharmendra Sharma
Austr. J. Intelligent Information Processing Systemsvol. 3
2009
Priority WatermarkingBased Face-Fingerprint Authentication System
Tuan Hoang, Dat Tran, Dhamendra Sharma, Trung Le, Bac Hoai Le
ICIMT
A Generic Framework for Soft Subspace Pattern Recognition
Dat Tran, Dhamendra Sharma Wanli Ma, Len Bui, Trung Le
Theory and Novel Applications of Machine Learning
For the complete and most up-to-date list, see Google Scholar.