Dinh Q. Phung - RankMe

395 papers A* 49A 28B 33C 16Misc 5Journal 180Unranked 81

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LiveCultureBench: a Multi-Agent, Multi-Cultural Benchmark for Large Language Models in Dynamic Social Simulations. CoRR Viet-Thanh Pham, Lizhen Qu, Thuy-Trang Vu, Gholamreza Haffari, Dinh Q. Phung
2026	J	`jnl`	Sharpness-Aware Minimization in Logit Space Efficiently Enhances Direct Preference Optimization. CoRR Haocheng Luo, Zehang Deng, Thanh-Toan Do, Mehrtash Harandi, Dinh Q. Phung, Trung Le
2026	J	`jnl`	Test-Time Instance-Specific Parameter Composition: A New Paradigm for Adaptive Generative Modeling. CoRR Minh-Tuan Tran, Xuan-May Le, Quan Hung Tran, Mehrtash Harandi, Dinh Q. Phung, Trung Le
2025	A*	`conf`	Boosting Multiple Views for pretrained-based Continual Learning. ICLR Quyen Tran, Tung Lam Tran, Khanh Doan, Toan Tran, Dinh Q. Phung, Khoat Than, Trung Le
2025	J	`jnl`	DeepVulMatch: Learning and Matching Latent Vulnerability Representations for Dual-Granularity Vulnerability Detection. IEEE Trans. Reliab. Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Q. Phung
2025	A*	`conf`	Enhancing Dataset Distillation via Non-Critical Region Refinement. CVPR Minh-Tuan Tran, Trung Le, Xuan-May Le, Thanh-Toan Do, Dinh Q. Phung
2025	J	`jnl`	Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization. CoRR Haocheng Luo, Tuan Truong, Tung Pham, Mehrtash Harandi, Dinh Q. Phung, Trung Le
2025	J	`jnl`	Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them. CoRR Anh Bui, Trang Vu, Tung-Long Vuong, Trung Le, Paul Montague, Tamas Abraham, Junae Kim, Dinh Q. Phung
2025	J	`jnl`	G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge. CoRR Linhao Luo, Zicheng Zhao, Junnan Liu, Zhangchi Qiu, Junnan Dong, Serge Panev, Chen Gong, Thuy-Trang Vu, Gholamreza Haffari, Dinh Q. Phung, Alan Wee-Chung Liew, Shirui Pan
2025	J	`jnl`	GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation. CoRR Linhao Luo, Zicheng Zhao, Gholamreza Haffari, Dinh Q. Phung, Chen Gong, Shirui Pan
2025	J	`jnl`	HVQ-VAE: Variational auto-encoder with hyperbolic vector quantization. Comput. Vis. Image Underst. Shangyu Chen, Pengfei Fang, Mehrtash Harandi, Trung Le, Jianfei Cai, Dinh Q. Phung
2025	J	`jnl`	Improving Table Understanding with LLMs and Entity-Oriented Search. CoRR Thi-Nhung Nguyen, Hoang Ngo, Dinh Q. Phung, Thuy-Trang Vu, Dat Quoc Nguyen
2025	J	`jnl`	LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. Trans. Assoc. Comput. Linguistics Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du
2025	J	`jnl`	Mitigating Semantic Collapse in Generative Personalization with a Surprisingly Simple Test-Time Embedding Adjustment. CoRR Anh Bui, Trang Vu, Trung Le, Junae Kim, Tamas Abraham, Rollin Omari, Amar Kaur, Dinh Q. Phung
2025	J	`jnl`	Optimizing Specific and Shared Parameters for Efficient Parameter Tuning. CoRR Van-Anh Nguyen, Thanh-Toan Do, Mehrtash Harandi, Dinh Q. Phung, Trung Le
2025	A*	`conf`	PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction. ICLR Shangyu Chen, Zizheng Pan, Jianfei Cai, Dinh Q. Phung
2025	A*	`conf`	PanSplat: 4K Panorama Synthesis with Feed-Forward Gaussian Splatting. CVPR Cheng Zhang, Haofei Xu, Qianyi Wu, Camilo Cruz Gambardella, Dinh Q. Phung, Jianfei Cai
2025	J	`jnl`	Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation. CoRR Tung-Long Vuong, Hoang Phan, Vy Vo, Anh Bui, Thanh-Toan Do, Trung Le, Dinh Q. Phung
2025	J	`jnl`	Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models. CoRR Ngoc-Quan Pham, Tuan Truong, Quyen Tran, Tan Nguyen, Dinh Q. Phung, Trung Le
2025	J	`jnl`	The Social Cost of Intelligence: Emergence, Propagation, and Amplification of Stereotypical Bias in Multi-Agent Systems. CoRR Thi-Nhung Nguyen, Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung
2025	J	`jnl`	Unbiased Sliced Wasserstein Kernels for High-Quality Audio Captioning. CoRR Manh Luong, Khai Nguyen, Dinh Q. Phung, Gholamreza Haffari, Lizhen Qu
2025	J	`jnl`	Unified Camera Positional Encoding for Controlled Video Generation. CoRR Cheng Zhang, Boying Li, Meng Wei, Yan-Pei Cao, Camilo Cruz Gambardella, Dinh Q. Phung, Jianfei Cai
2025	J	`jnl`	Why Domain Generalization Fail? A View of Necessity and Sufficiency. CoRR Long Tung Vuong, Vy Vo, Hien Dang, Van-Anh Nguyen, Thanh-Toan Do, Mehrtash Harandi, Trung Le, Dinh Q. Phung
2024	J	`jnl`	A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation. CoRR Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung
2024	J	`jnl`	AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities. Empir. Softw. Eng. Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Yuki Kume, Van Nguyen, Dinh Q. Phung, John C. Grundy
2024	—	`conf`	Active Continual Learning: On Balancing Knowledge Retention and Learnability. AI (2) Thuy-Trang Vu, Shahram Khadivi, Mahsa Ghorbanali, Dinh Q. Phung, Gholamreza Haffari
2024	—	`conf`	CA-OVS: Cluster and Adapt Mask Proposals for Open-Vocabulary Semantic Segmentation. MMAsia Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai
2024	J	`jnl`	Class Enhancement Losses With Pseudo Labels for Open-Vocabulary Semantic Segmentation. IEEE Trans. Multim. Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai
2024	J	`jnl`	Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection. ACM Trans. Softw. Eng. Methodol. Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Dinh Q. Phung
2024	J	`jnl`	Diversity-Aware Agnostic Ensemble of Sharpness Minimizers. CoRR Anh Bui, Vy Vo, Tung Pham, Dinh Q. Phung, Trung Le
2024	A*	`conf`	Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation. NeurIPS Anh Bui, Tung-Long Vuong, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung
2024	J	`jnl`	Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation. CoRR Anh Bui, Long Tung Vuong, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung
2024	A*	`conf`	Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization. NeurIPS Haocheng Luo, Tuan Truong, Tung Pham, Mehrtash Harandi, Dinh Q. Phung, Trung Le
2024	A	`conf`	Frequency Attention for Knowledge Distillation. WACV Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do
2024	J	`jnl`	Frequency Attention for Knowledge Distillation. CoRR Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do
2024	J	`jnl`	LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. CoRR Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du
2024	J	`jnl`	Large-Scale Data-Free Knowledge Distillation for ImageNet via Multi-Resolution Data Generation. CoRR Minh-Tuan Tran, Trung Le, Xuan-May Le, Jianfei Cai, Mehrtash Harandi, Dinh Q. Phung
2024	J	`jnl`	Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. CoRR Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do
2024	A*	`conf`	NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation. CVPR Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Quan Hung Tran, Dinh Q. Phung
2024	—	`conf`	Neural Topic Model with Distance Awareness. ICPR (9) Shangyu Chen, He Zhao, Viet H. Huynh, Dinh Q. Phung, Jianfei Cai
2024	J	`jnl`	Neural Topic Modeling with Large Language Models in the Loop. CoRR Xiaohao Yang, He Zhao, Weijie Xu, Yuanyuan Qi, Jueqing Lu, Dinh Q. Phung, Lan Du
2024	J	`jnl`	Optimal Transport for Structure Learning Under Missing Data. CoRR Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung
2024	J	`jnl`	PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction. CoRR Shangyu Chen, Zizheng Pan, Jianfei Cai, Dinh Q. Phung
2024	J	`jnl`	PanSplat: 4K Panorama Synthesis with Feed-Forward Gaussian Splatting. CoRR Cheng Zhang, Haofei Xu, Qianyi Wu, Camilo Cruz Gambardella, Dinh Q. Phung, Jianfei Cai
2024	J	`jnl`	Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts. CoRR Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung
2024	J	`jnl`	Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. CoRR Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Q. Phung, Lizhen Qu
2024	—	`conf`	Stereographic Projection for Embedding Hierarchical Structures in Hyperbolic Space. ICPR (9) Shangyu Chen, Xiaohao Yang, Pengfei Fang, Mehrtash Tafazzoli Harandi, Dinh Q. Phung, Jianfei Cai
2024	J	`jnl`	Taming Stable Diffusion for Text to 360{\deg} Panorama Image Generation. CoRR Cheng Zhang, Qianyi Wu, Camilo Cruz Gambardella, Xiaoshui Huang, Dinh Q. Phung, Wanli Ouyang, Jianfei Cai
2023	J	`jnl`	Active Continual Learning: Labelling Queries in a Sequence of Tasks. CoRR Thuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza Haffari
2023	J	`jnl`	Building and Nurturing AI Development in Vietnam. Commun. ACM Hung Bui, Nguyen Minh Le, Dat Quoc Nguyen, Linh Pham, Dinh Q. Phung
2023	J	`jnl`	Class Enhancement Losses with Pseudo Labels for Zero-shot Semantic Segmentation. CoRR Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai
2023	J	`jnl`	Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay. CoRR Khanh Doan, Quyen Tran, Tuan Nguyen, Dinh Q. Phung, Trung Le
2023	J	`jnl`	Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai
2023	—	`conf`	Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation. MICCAI (1) Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung
2023	J	`jnl`	Cross-adversarial local distribution regularization for semi-supervised medical image segmentation. CoRR Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung
2023	A*	`conf`	Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. KDD Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung
2023	A*	`conf`	Flat Seeking Bayesian Neural Networks. NeurIPS Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le
2023	J	`jnl`	Flat Seeking Bayesian Neural Networks. CoRR Van-Anh Nguyen, Long Tung Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le
2023	J	`jnl`	Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. CoRR Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Q. Phung
2023	A	`conf`	Global-Local Regularization Via Distributional Robustness. AISTATS Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung
2023	J	`jnl`	Hyperbolic Geometry in Computer Vision: A Survey. CoRR Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Q. Phung
2023	J	`jnl`	KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All. CoRR Quyen Tran, Lam Tran, Khoat Than, Toan Tran, Dinh Q. Phung, Trung Le
2023	J	`jnl`	Learning Directed Graphical Models with Optimal Transport. CoRR Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Q. Phung
2023	J	`jnl`	Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities. CoRR Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Q. Phung
2023	Misc	`conf`	On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks. ICASSP Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho
2023	A*	`conf`	Optimal Transport Model Distributional Robustness. NeurIPS Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung
2023	J	`jnl`	Optimal Transport Model Distributional Robustness. CoRR Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung
2023	J	`jnl`	PhoGPT: Generative Pre-training for Vietnamese. CoRR Dat Quoc Nguyen, Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, Nhung Nguyen, Thien Huu Nguyen, Dinh Q. Phung, Hung Hai Bui
2023	J	`jnl`	Robust Contrastive Learning With Theory Guarantee. CoRR Ngoc N. Tran, Lam Tran, Hoang Phan, Anh Tuan Bui, Tung Pham, Toan Tran, Dinh Q. Phung, Trung Le
2023	J	`jnl`	Sharpness & Shift-Aware Self-Supervised Learning. CoRR Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Q. Phung, Trung Le
2023	—	`conf`	Systematic Assessment of Factual Knowledge in Large Language Models. EMNLP (Findings) Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung, Gholamreza Haffari
2023	J	`jnl`	Systematic Assessment of Factual Knowledge in Large Language Models. CoRR Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung, Gholamreza Haffari
2023	B	`conf`	Two-View Graph Neural Networks for Knowledge Graph Completion. ESWC Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen
2023	J	`jnl`	Unleash Data Generation for Efficient and Effective Data-free Knowledge Distillation. CoRR Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Quan Hung Tran, Dinh Q. Phung
2023	A*	`conf`	Vector Quantized Wasserstein Auto-Encoder. ICML Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
2023	J	`jnl`	Vector Quantized Wasserstein Auto-Encoder. CoRR Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
2023	J	`jnl`	VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types. IEEE Trans. Software Eng. Michael Fu, Van Nguyen, Chakkrit Kla Tantithamthavorn, Trung Le, Dinh Q. Phung
2022	A*	`conf`	A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
2022	J	`jnl`	A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR Tuan-Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
2022	A	`conf`	A Vietnamese-English Neural Machine Translation System. INTERSPEECH 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
2022	J	`jnl`	An Additive Instance-Wise Approach to Multi-class Model Interpretation. CoRR Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Q. Phung
2022	J	`jnl`	An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability. CoRR Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Hung Nguyen, Seyit Camtepe, Paul Quirk, Dinh Q. Phung
2022	A*	`conf`	Bridging Global Context Interactions for High-Fidelity Image Completion. CVPR Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung
2022	J	`jnl`	Can Domains Be Transferred Across Languages in Multi-Domain Multilingual Neural Machine Translation? CoRR Thuy-Trang Vu, Shahram Khadivi, Xuanli He, Dinh Q. Phung, Gholamreza Haffari
2022	J	`jnl`	Continual Learning with Optimal Transport based Mixture Model. CoRR Quyen Tran, Hoang Phan, Khoat Than, Dinh Q. Phung, Trung Le
2022	J	`jnl`	Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle. CoRR Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Hung Nguyen, Dinh Q. Phung
2022	A	`conf`	Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. UAI Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung
2022	—	`conf`	Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out Training. ACL (Findings) Thuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza Haffari
2022	J	`jnl`	Global-Local Regularization Via Distributional Robustness. CoRR Hoang Phan, Trung Le, Trung Phung, Tuan-Anh Bui, Nhat Ho, Dinh Q. Phung
2022	J	`jnl`	High-Quality Pluralistic Image Completion via Code Shared VQGAN. CoRR Chuanxia Zheng, Guoxian Song, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung, Linjie Luo
2022	J	`jnl`	Improving Multi-task Learning via Seeking Task-based Flat Regions. CoRR Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Q. Phung, Trung Le
2022	J	`jnl`	Improving kernel online learning with a snapshot memory. Mach. Learn. Trung Le, Khanh Nguyen, Dinh Q. Phung
2022	J	`jnl`	Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. CoRR Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung
2022	J	`jnl`	MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. CoRR Chuanxia Zheng, Long Tung Vuong, Jianfei Cai, Dinh Q. Phung
2022	J	`jnl`	Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance. CoRR Ngoc N. Tran, Anh Tuan Bui, Dinh Q. Phung, Trung Le
2022	A	`conf`	Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction. WSDM Dai Quoc Nguyen, Vinh Tong, Dinh Q. Phung, Dat Quoc Nguyen
2022	A	`conf`	On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds. AISTATS Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Hung Tran, Dinh Q. Phung
2022	A	`conf`	Particle-based Adversarial Local Distribution Regularization. AISTATS Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung
2022	—	`conf`	QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. WWW (Companion Volume) Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Q. Phung
2022	J	`jnl`	Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. CoRR Tam Le, Truyen Nguyen, Dinh Q. Phung, Viet Anh Nguyen
2022	—	`conf`	Universal Graph Transformer Self-Attention Networks. WWW (Companion Volume) Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2022	—	`conf`	Vietnamese Speech-based Question Answering over Car Manuals. IUI Companion 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
2022	J	`jnl`	Vision Transformer Visualization: What Neurons Tell and How Neurons Behave? CoRR Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong, Thanh-Toan Do, Quan Hung Tran, Dinh Q. Phung, Trung Le
2022	—	`conf`	VulRepair: a T5-based automated software vulnerability repair. ESEC/SIGSOFT FSE Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, Dinh Q. Phung
2021	A*	`conf`	Exploiting Domain-Specific Features to Enhance Domain Generalization. NeurIPS Manh-Ha Bui, Toan Tran, Anh Tran, Dinh Q. Phung
2021	—	`conf`	Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection. EMNLP (1) Thuy-Trang Vu, Xuanli He, Dinh Q. Phung, Gholamreza Haffari
2021	J	`jnl`	Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection. CoRR Thuy-Trang Vu, Xuanli He, Dinh Q. Phung, Gholamreza Haffari
2021	A	`conf`	Most: multi-source domain adaptation via optimal transport for student-teacher learning. UAI Tuan Nguyen, Trung Le, He Zhao, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung
2021	J	`jnl`	On Label Shift in Domain Adaptation via Wasserstein Distance. CoRR Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung
2021	A*	`conf`	On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. NeurIPS Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung
2021	J	`jnl`	On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2021	A*	`conf`	Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI Viet Huynh, Dinh Q. Phung, He Zhao
2021	C	`conf`	Quaternion Graph Neural Networks. ACML Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2021	J	`jnl`	ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection. CoRR Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Q. Phung
2021	A*	`conf`	TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport. IJCAI Tuan Nguyen, Trung Le, Nhan Dam, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung
2021	A*	`conf`	Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
2021	J	`jnl`	Two-view Graph Neural Networks for Knowledge Graph Completion. CoRR Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen
2020	—	`conf`	Improving Adversarial Robustness by Enforcing Local and Global Compactness. ECCV (27) Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Q. Phung
2019	—	`conf`	A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. NAACL-HLT (1) Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
2019	B	`conf`	Deep Domain Adaptation for Vulnerable Code Function Identification. IJCNN Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier Y. DeVel, Paul Montague, Lizhen Qu, Dinh Q. Phung
2019	J	`jnl`	GoGP: scalable geometric-based Gaussian process for online regression. Knowl. Inf. Syst. Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2019	A*	`conf`	Learning Generative Adversarial Networks from Multiple Data Sources. IJCAI Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung
2019	—	`conf`	Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection. ICLR (Poster) Tue Le, Tuan Nguyen, Trung Le, Dinh Q. Phung, Paul Montague, Olivier Y. de Vel, Lizhen Qu
2019	J	`jnl`	On Efficient Multilevel Clustering via Wasserstein Distances. CoRR Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2019	J	`jnl`	On Scalable Variant of Wasserstein Barycenter. CoRR Tam Le, Viet Huynh, Nhat Ho, Dinh Q. Phung, Makoto Yamada
2019	A	`conf`	Probabilistic Multilevel Clustering via Composite Transportation Distance. AISTATS Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan
2019	J	`jnl`	Relational Memory-based Knowledge Graph Embedding. CoRR Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2019	A*	`conf`	Robust Anomaly Detection in Videos Using Multilevel Representations. AAAI Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung
2019	J	`jnl`	When Can Neural Networks Learn Connected Decision Regions? CoRR Trung Le, Dinh Q. Phung
2018	J	`jnl`	A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. CoRR Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
2018	—	`conf`	A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. NAACL-HLT (2) Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
2018	J	`jnl`	Academia versus social media: A psycho-linguistic analysis. J. Comput. Sci. Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2018	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part I PAKDD (1) Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi
2018	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part II PAKDD (2) Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi
2018	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part III PAKDD (3) Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi
2018	C	`conf`	Batch Normalized Deep Boltzmann Machines. ACML Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung
2018	B	`conf`	Bayesian Multi-Hyperplane Machine for Pattern Recognition. ICPR Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung
2018	C	`conf`	Clustering Induced Kernel Learning. ACML Khanh Nguyen, Nhan Dam, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung
2018	J	`jnl`	Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models. CoRR Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung
2018	J	`jnl`	Discovering topic structures of a temporally evolving document corpus. Knowl. Inf. Syst. Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh
2018	J	`jnl`	Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding. J. Medical Syst. Dang Nguyen, Wei Luo, Svetha Venkatesh, Dinh Q. Phung
2018	A*	`conf`	Geometric Enclosing Networks. IJCAI Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung
2018	—	`conf`	Jointly Predicting Affective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web. WISE (2) Hung Nguyen, Van Nguyen, Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Duc Thanh Nguyen, Trung Le, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen
2018	J	`jnl`	LTARM: A novel temporal association rule mining method to understand toxicities in a routine cancer treatment. Knowl. Based Syst. Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh
2018	A	`conf`	Learning Graph Representation via Frequent Subgraphs. SDM Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung
2018	—	`conf`	MGAN: Training Generative Adversarial Nets with Multiple Generators. ICLR (Poster) Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung
2018	J	`jnl`	Model-based learning for point pattern data. Pattern Recognit. Ba-Ngu Vo, Nhan Dam, Dinh Q. Phung, Quang N. Tran, Ba-Tuong Vo
2018	J	`jnl`	Probabilistic Multilevel Clustering via Composite Transportation Distance. CoRR Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan
2018	A*	`conf`	Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data. KDD Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, Geoffrey I. Webb
2018	—	`conf`	Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint. ECML/PKDD (2) Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung
2018	J	`jnl`	Theoretical Perspective of Deep Domain Adaptation. CoRR Trung Le, Khanh Nguyen, Dinh Q. Phung
2017	J	`jnl`	A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare. IEEE J. Biomed. Health Informatics Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2017	J	`jnl`	A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. CoRR Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
2017	J	`jnl`	A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process. Pervasive Mob. Comput. Nguyen Cong Thuong, Vu Nguyen, Flora D. Salim, Duc Viet Le, Dinh Q. Phung
2017	J	`jnl`	Analogical-based Bayesian Optimization. CoRR Trung Le, Khanh Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2017	B	`conf`	Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring. DSAA Hung Nguyen, Sarah J. Maclagan, Tu Dinh Nguyen, Thin Nguyen, Paul Flemons, Kylie Andrews, Euan G. Ritchie, Dinh Q. Phung
2017	J	`jnl`	Approximation Vector Machines for Large-scale Online Learning. J. Mach. Learn. Res. Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2017	J	`jnl`	Clustering For Point Pattern Data. CoRR Quang N. Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo
2017	A*	`conf`	Column Networks for Collective Classification. AAAI Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2017	A*	`conf`	Discriminative Bayesian Nonparametric Clustering. IJCAI Vu Nguyen, Dinh Q. Phung, Trung Le, Hung Bui
2017	—	`conf`	Dual Discriminator Generative Adversarial Nets. NIPS Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung
2017	J	`jnl`	Dual Discriminator Generative Adversarial Nets. CoRR Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung
2017	J	`jnl`	Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions. Knowl. Inf. Syst. Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2017	—	`conf`	Energy-Based Localized Anomaly Detection in Video Surveillance. PAKDD (1) Hung Vu, Tu Dinh Nguyen, Anthony Travers, Svetha Venkatesh, Dinh Q. Phung
2017	J	`jnl`	Energy-based Models for Video Anomaly Detection. CoRR Hung Vu, Dinh Q. Phung, Tu Dinh Nguyen, Anthony Trevors, Svetha Venkatesh
2017	—	`conf`	Estimating Support Scores of Autism Communities in Large-Scale Web Information Systems. WISE (1) Thin Nguyen, Nguyen Hung, Svetha Venkatesh, Dinh Q. Phung
2017	J	`jnl`	Estimation of the prevalence of adverse drug reactions from social media. Int. J. Medical Informatics Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen
2017	B	`conf`	Forward-Backward Smoothing for Hidden Markov Models of Point Pattern Data. DSAA Nhan Dam, Dinh Q. Phung, Ba-Ngu Vo, Viet Huynh
2017	J	`jnl`	Geometric Enclosing Networks. CoRR Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung
2017	A*	`conf`	GoGP: Fast Online Regression with Gaussian Processes. ICDM Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2017	J	`jnl`	KGAN: How to Break The Minimax Game in GAN. CoRR Trung Le, Tu Dinh Nguyen, Dinh Q. Phung
2017	J	`jnl`	Kernel-based features for predicting population health indices from geocoded social media data. Decis. Support Syst. Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Duc Thanh Nguyen, John Yearwood, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen
2017	A*	`conf`	Large-scale Online Kernel Learning with Random Feature Reparameterization. IJCAI Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung
2017	J	`jnl`	Latent sentiment topic modelling and nonparametric discovery of online mental health-related communities. Int. J. Data Sci. Anal. Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2017	J	`jnl`	Model-Based Multiple Instance Learning. CoRR Ba-Ngu Vo, Dinh Q. Phung, Quang N. Tran, Ba-Tuong Vo
2017	J	`jnl`	Model-based Classification and Novelty Detection For Point Pattern Data. CoRR Ba-Ngu Vo, Quang N. Tran, Dinh Q. Phung, Ba-Tuong Vo
2017	J	`jnl`	Multi-Generator Generative Adversarial Nets. CoRR Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung
2017	A*	`conf`	Multilevel Clustering via Wasserstein Means. ICML Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung
2017	J	`jnl`	Multiple Instance Learning with the Optimal Sub-Pattern Assignment Metric. CoRR Quang N. Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo, Nguyen Cong Thuong
2017	J	`jnl`	Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization. CoRR Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2017	J	`jnl`	Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data. Knowl. Inf. Syst. Pratibha Vellanki, Thi V. Duong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2017	J	`jnl`	Predicting healthcare trajectories from medical records: A deep learning approach. J. Biomed. Informatics Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2017	—	`conf`	Prediction of Population Health Indices from Social Media using Kernel-based Textual and Temporal Features. WWW (Companion Volume) Thin Nguyen, Duc Thanh Nguyen, Mark E. Larsen, Bridianne O'Dea, John Yearwood, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen
2017	J	`jnl`	Statistical Latent Space Approach for Mixed Data Modelling and Applications. CoRR Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2017	J	`jnl`	Streaming clustering with Bayesian nonparametric models. Neurocomputing Viet Huynh, Dinh Q. Phung
2017	A	`conf`	Supervised Restricted Boltzmann Machines. UAI Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le
2017	J	`jnl`	Using linguistic and topic analysis to classify sub-groups of online depression communities. Multim. Tools Appl. Thin Nguyen, Bridianne O'Dea, Mark E. Larsen, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen
2016	J	`jnl`	A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression. IEEE J. Biomed. Health Informatics Budhaditya Saha, Thin Nguyen, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	A new transfer learning framework with application to model-agnostic multi-task learning. Knowl. Inf. Syst. Sunil Gupta, Santu Rana, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments. CoRR Nguyen Cong Thuong, Truyen Tran, Shivapratap Gopakumar, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	Analysing the History of Autism Spectrum Disorder Using Topic Models. DSAA Adham Beykikhoshk, Dinh Q. Phung, Ognjen Arandjelovic, Svetha Venkatesh
2016	J	`jnl`	Approximation Vector Machines for Large-scale Online Learning. CoRR Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2016	A	`conf`	Budgeted Semi-supervised Support Vector Machine . UAI Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2016	J	`jnl`	Choice by Elimination via Deep Neural Networks. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	Clustering for point pattern data. ICPR Nhat-Quang Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo
2016	J	`jnl`	Collaborative filtering via sparse Markov random fields. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Collaborative filtering via sparse Markov random fields. Inf. Sci. Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Column Networks for Collective Classification. CoRR Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	Misc	`conf`	Computer assisted autism interventions for India. OZCHI Pratibha Vellanki, Stewart Greenhill, Thi V. Duong, Dinh Q. Phung, Svetha Venkatesh, Jayashree Godwin, Krishnaveni Achary, Blessin Varkey
2016	J	`jnl`	Control Matching via Discharge Code Sequences. CoRR Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh
2016	—	`conf`	Data Mining of Intervention for Children with Autism Spectrum Disorder. eHealth 360° Pratibha Vellanki, Thi V. Duong, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Data clustering using side information dependent Chinese restaurant processes. Knowl. Inf. Syst. Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2016	—	`conf`	DeepCare: A Deep Dynamic Memory Model for Predictive Medicine. PAKDD (2) Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	DeepCare: A Deep Dynamic Memory Model for Predictive Medicine. CoRR Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	A	`conf`	Discovering latent affective dynamics among individuals in online mental health-related communities. ICME Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	—	`conf`	Discriminative Cues for Different Stages of Smoking Cessation in Online Community. WISE (2) Thin Nguyen, Ron Borland, John Yearwood, Hua-Hie Yong, Svetha Venkatesh, Dinh Q. Phung
2016	B	`conf`	Distributed data augmented support vector machine on Spark. ICPR Tu Dinh Nguyen, Vu Nguyen, Trung Le, Dinh Q. Phung
2016	—	`conf`	Dual Space Gradient Descent for Online Learning. NIPS Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2016	—	`conf`	Effect of social capital on emotion, language style and latent topics in online depression community. RIVF Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	—	`conf`	Exceptional Contrast Set Mining: Moving Beyond the Deluge of the Obvious. Australasian Conference on Artificial Intelligence Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Faster Training of Very Deep Networks Via p-Norm Gates. CoRR Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	Faster training of very deep networks via p-norm gates. ICPR Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	—	`conf`	Forecasting Patient Outflow from Wards having No Real-Time Clinical Data. ICHI Shivapratap Gopakumar, Truyen Tran, Wei Luo, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Graph-induced restricted Boltzmann machines for document modeling. Inf. Sci. Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records. Knowl. Based Syst. Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Introduction: special issue of selected papers from ACML 2014. Mach. Learn. Hang Li, Dinh Q. Phung, Tru H. Cao, Tu Bao Ho, Zhi-Hua Zhou
2016	—	`conf`	Large-Scale Stylistic Analysis of Formality in Academia and Social Media. WISE (2) Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	—	`conf`	Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes. PAKDD Workshops Nguyen Thanh Binh, Vu Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	B	`conf`	Learning Multifaceted Latent Activities from Heterogeneous Mobile Data. DSAA Nguyen Thanh Binh, Vu Nguyen, Nguyen Cong Thuong, Svetha Venkatesh, Mohan Kumar, Dinh Q. Phung
2016	J	`jnl`	Learning deep representation of multityped objects and tasks. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	MCNC: Multi-Channel Nonparametric Clustering from heterogeneous data. ICPR Nguyen Thanh Binh, Vu Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	B	`conf`	Model-based classification and novelty detection for point pattern data. ICPR Ba-Ngu Vo, Nhat-Quang Tran, Dinh Q. Phung, Ba-Tuong Vo
2016	J	`jnl`	Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach. Knowl. Inf. Syst. Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Modelling multilevel data in multimedia: A hierarchical factor analysis approach. Multim. Tools Appl. Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2016	C	`conf`	Multiple Kernel Learning with Data Augmentation. ACML Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2016	J	`jnl`	Multiple task transfer learning with small sample sizes. Knowl. Inf. Syst. Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2016	—	`conf`	Neural Choice by Elimination via Highway Networks. PAKDD Workshops Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	A	`conf`	Nonparametric Budgeted Stochastic Gradient Descent. AISTATS Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2016	J	`jnl`	Nonparametric discovery of movement patterns from accelerometer signals. Pattern Recognit. Lett. Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2016	A*	`conf`	One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems. ICDM Vu Nguyen, Tu Dinh Nguyen, Trung Le, Svetha Venkatesh, Dinh Q. Phung
2016	C	`conf`	Outlier Detection on Mixed-Type Data: An Energy-Based Approach. ADMA Kien Do, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Outlier Detection on Mixed-Type Data: An Energy-based Approach. CoRR Kien Do, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	—	`conf`	Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data. MLHC Truyen Tran, Wei Luo, Dinh Q. Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh
2016	A*	`conf`	SECC: Simultaneous extraction of context and community from pervasive signals. PerCom Nguyen Cong Thuong, Vu Nguyen, Flora D. Salim, Dinh Q. Phung
2016	A	`conf`	Scalable Nonparametric Bayesian Multilevel Clustering. UAI Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui
2016	J	`jnl`	Scalable Support Vector Machine for Semi-supervised Learning. CoRR Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Q. Phung
2016	—	`conf`	Sparse Adaptive Multi-hyperplane Machine. PAKDD (1) Khanh Nguyen, Trung Le, Vu Nguyen, Dinh Q. Phung
2016	C	`conf`	Stabilizing Linear Prediction Models Using Autoencoder. ADMA Shivapratap Gopakumar, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Stabilizing l J. Biomed. Informatics Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	Stable clinical prediction using graph support vector machines. ICPR Iman Kamkar, Sunil Gupta, Cheng Li, Dinh Q. Phung, Svetha Venkatesh
2016	C	`conf`	Textual Cues for Online Depression in Community and Personal Settings. ADMA Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	—	`conf`	Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. PAKDD (1) Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely, Dinh Q. Phung
2016	B	`conf`	Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model. ICPR Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	A Bayesian Nonparametric Approach to Multilevel Regression. PAKDD (1) Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
2015	J	`jnl`	A predictive framework for modeling healthcare data with evolving clinical interventions. Stat. Anal. Data Min. Santu Rana, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	A study on the stability of EEG signals for user authentication. NER Tien Pham, Wanli Ma, Dat Tran, Duc Su Tran, Dinh Q. Phung
2015	J	`jnl`	Autism Blogs: Expressed Emotion, Language Styles and Concerns in Personal and Community Settings. IEEE Trans. Affect. Comput. Thin Nguyen, Thi V. Duong, Svetha Venkatesh, Dinh Q. Phung
2015	—	`conf`	Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning. PAKDD (1) Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Conditional Entropy Approach to Multichannel EEG-Based Person Identification. CISIS-ICEUTE Dinh Q. Phung, Dat Tran, Wanli Ma, Tien Pham
2015	—	`conf`	Differentiating Sub-groups of Online Depression-Related Communities Using Textual Cues. WISE (2) Thin Nguyen, Bridianne O'Dea, Mark E. Larsen, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen
2015	J	`jnl`	Discovering topic structures of a temporally evolving document corpus. CoRR Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh
2015	B	`conf`	Exploiting feature relationships towards stable feature selection. DSAA Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Fast One-Class Support Vector Machine for Novelty Detection. PAKDD (2) Trung Le, Dinh Q. Phung, Khanh Nguyen, Svetha Venkatesh
2015	—	`conf`	Hierarchical Dirichlet Process for Tracking Complex Topical Structure Evolution and Its Application to Autism Research Literature. PAKDD (1) Adham Beykikhoshk, Ognjen Arandjelovic, Svetha Venkatesh, Dinh Q. Phung
2015	J	`jnl`	Hierarchical Dirichlet process for tracking complex topical structure evolution and its application to autism research literature. CoRR Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. CISIS-ICEUTE Dinh Q. Phung, Dat Tran, Wanli Ma, Tien Pham
2015	—	`conf`	Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
2015	—	`conf`	Learning Entry Profiles of Children with Autism from Multivariate Treatment Information Using Restricted Boltzmann Machines. PAKDD Workshops Pratibha Vellanki, Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh
2015	J	`jnl`	Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM). J. Biomed. Informatics Truyen Tran, Tu Dinh Nguyen, Dinh Q. Phung, Svetha Venkatesh
2015	J	`jnl`	Mixed-norm sparse representation for multi view face recognition. Pattern Recognit. Xin Zhang, Duc-Son Pham, Svetha Venkatesh, Wanquan Liu, Dinh Q. Phung
2015	Misc	`conf`	Multi-View Subspace Clustering for Face Images. DICTA Xin Zhang, Dinh Q. Phung, Svetha Venkatesh, Duc-Son Pham, Wanquan Liu
2015	B	`conf`	Nonparametric discovery of online mental health-related communities. DSAA Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2015	B	`conf`	Overcoming Data Scarcity of Twitter: Using Tweets as Bootstrap with Application to Autism-Related Topic Content Analysis. ASONAM Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh
2015	J	`jnl`	Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis. CoRR Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. PAKDD (2) Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2015	J	`jnl`	Stabilized sparse ordinal regression for medical risk stratification. Knowl. Inf. Syst. Truyen Tran, Dinh Q. Phung, Wei Luo, Svetha Venkatesh
2015	J	`jnl`	Stabilizing High-Dimensional Prediction Models Using Feature Graphs. IEEE J. Biomed. Health Informatics Shivapratap Gopakumar, Truyen Tran, Tu Dinh Nguyen, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records. PAKDD (2) Shivapratap Gopakumar, Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Stable Feature Selection with Support Vector Machines. Australasian Conference on Artificial Intelligence Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2015	J	`jnl`	Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso. J. Biomed. Informatics Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2015	C	`conf`	Streaming Variational Inference for Dirichlet Process Mixtures. ACML Viet Huynh, Dinh Q. Phung, Svetha Venkatesh
2015	A*	`conf`	Tensor-Variate Restricted Boltzmann Machines. AAAI Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2015	J	`jnl`	Tree-based iterated local search for Markov random fields with applications in image analysis. J. Heuristics Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2015	—	`conf`	Understanding Toxicities and Complications of Cancer Treatment: A Data Mining Approach. Australasian Conference on Artificial Intelligence Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh
2015	J	`jnl`	Using Twitter to learn about the autism community. CoRR Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh, Terry Caelli
2015	J	`jnl`	Using Twitter to learn about the autism community. Soc. Netw. Anal. Min. Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh, Terry Caelli
2015	A	`conf`	Visual Object Clustering via Mixed-Norm Regularization. WACV Xin Zhang, Duc-Son Pham, Dinh Q. Phung, Wanquan Liu, Budhaditya Saha, Svetha Venkatesh
2015	A	`conf`	What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. SDM Sunil Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2014	B	`conf`	A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data. ICPR Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2014	J	`jnl`	A framework for feature extraction from hospital medical data with applications in risk prediction. BMC Bioinform. Truyen Tran, Wei Luo, Dinh Q. Phung, Sunil Gupta, Santu Rana, Richard Kennedy, Ann Larkins, Svetha Venkatesh
2014	C	`conf`	A random finite set model for data clustering. FUSION Dinh Q. Phung, Ba-Ngu Vo
2014	J	`jnl`	Affective and Content Analysis of Online Depression Communities. IEEE Trans. Affect. Comput. Thin Nguyen, Dinh Q. Phung, Bo Dao, Svetha Venkatesh, Michael Berk
2014	—	`conf`	Affective, Linguistic and Topic Patterns in Online Autism Communities. WISE (2) Thin Nguyen, Thi V. Duong, Dinh Q. Phung, Svetha Venkatesh
2014	B	`conf`	Analysis of circadian rhythms from online communities of individuals with affective disorders. DSAA Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung
2014	J	`jnl`	Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
2014	J	`jnl`	Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	B	`conf`	Data-mining twitter and the autism spectrum disorder: A Pilot study. ASONAM Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh, Terry Caelli
2014	—	`conf`	EEG-Based User Authentication Using Artifacts. SOCO-CISIS-ICEUTE Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung
2014	—	`conf`	Effect of Mood, Social Connectivity and Age in Online Depression Community via Topic and Linguistic Analysis. WISE (1) Bo Dao, Thin Nguyen, Dinh Q. Phung, Svetha Venkatesh
2014	A*	`conf`	Fixed-lag particle filter for continuous context discovery using Indian Buffet Process. PerCom Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2014	B	`conf`	Individualized arrhythmia detection with ECG signals from wearable devices. DSAA Nguyen Thanh Binh, Wei Luo, Terry Caelli, Svetha Venkatesh, Dinh Q. Phung
2014	—	`conf`	Intervention-Driven Predictive Framework for Modeling Healthcare Data. PAKDD (1) Santu Rana, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2014	B	`conf`	Investigating the impacts of epilepsy on EEG-based person identification systems. IJCNN Dinh Q. Phung, Dat Tran, Wanli Ma, Phuoc Nguyen, Tien Pham
2014	A	`conf`	Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions. SDM Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter. IEEE Trans. Signal Process. Ba-Ngu Vo, Ba-Tuong Vo, Dinh Q. Phung
2014	J	`jnl`	Learning From Ordered Sets and Applications in Collaborative Ranking. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Learning Rank Functionals: An Empirical Study. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Learning Structured Outputs from Partial Labels using Forest Ensemble. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	MCMC for Hierarchical Semi-Markov Conditional Random Fields. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
2014	J	`jnl`	Mixed-Variate Restricted Boltzmann Machines. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Mood sensing from social media texts and its applications. Knowl. Inf. Syst. Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2014	B	`conf`	Multi-factor EEG-based user authentication. IJCNN Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung
2014	B	`conf`	Nonparametric Discovery of Learning Patterns and Autism Subgroups from Therapeutic Data. ICPR Pratibha Vellanki, Thi V. Duong, Svetha Venkatesh, Dinh Q. Phung
2014	C	`conf`	Preface. ACML Dinh Q. Phung, Hang Li
2014	J	`jnl`	Preference Networks: Probabilistic Models for Recommendation Systems. CoRR Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
2014	C	`ed.`	Proceedings of the Sixth Asian Conference on Machine Learning, ACML 2014, Nha Trang City, Vietnam, November 26-28, 2014. ACML Dinh Q. Phung, Hang Li
2014	B	`conf`	Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. ICPR Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Social reader: towards browsing the social web. Multim. Tools Appl. Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Stabilizing Sparse Cox Model using Clinical Structures in Electronic Medical Records. CoRR Shivapratap Gopakumar, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Thurstonian Boltzmann Machines: Learning from Multiple Inequalities. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	J	`jnl`	Tree-based iterated local search for Markov random fields with applications in image analysis. CoRR Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2014	B	`conf`	Unsupervised inference of significant locations from WiFi data for understanding human dynamics. MUM Nguyen Thanh Binh, Nguyen Cong Thuong, Wei Luo, Svetha Venkatesh, Dinh Q. Phung
2014	B	`conf`	Using Shannon Entropy as EEG Signal Feature for Fast Person Identification. ESANN Dinh Q. Phung, Dat Tran, Wanli Ma, Phuoc Nguyen, Tien Pham
2014	—	`conf`	iPoll: Automatic Polling Using Online Search. WISE (1) Thin Nguyen, Dinh Q. Phung, Wei Luo, Truyen Tran, Svetha Venkatesh
2013	—	`conf`	A Study on the Feasibility of Using EEG Signals for Authentication Purpose. ICONIP (2) Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung
2013	A*	`conf`	An integrated framework for suicide risk prediction. KDD Truyen Tran, Dinh Q. Phung, Wei Luo, Richard Harvey, Michael Berk, Svetha Venkatesh
2013	A	`conf`	Analysis of psycholinguistic processes and topics in online autism communities. ICME Thin Nguyen, Dinh Q. Phung, Svetha Venkatesh
2013	—	`conf`	Clustering Patient Medical Records via Sparse Subspace Representation. PAKDD (2) Budhaditya Saha, Duc-Son Pham, Dinh Q. Phung, Svetha Venkatesh
2013	J	`jnl`	Connectivity, Online Social Capital, and Mood: A Bayesian Nonparametric Analysis. IEEE Trans. Multim. Dinh Q. Phung, Sunil Kumar Gupta, Thin Nguyen, Svetha Venkatesh
2013	J	`jnl`	Detection of cross-channel anomalies. Knowl. Inf. Syst. Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh
2013	—	`conf`	EEG-Based Age and Gender Recognition Using Tensor Decomposition and Speech Features. ICONIP (2) Phuoc Nguyen, Dat Tran, Tan Vo, Xu Huang, Wanli Ma, Dinh Q. Phung
2013	—	`conf`	EEG-Based User Authentication in Multilevel Security Systems. ADMA (2) Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung
2013	J	`jnl`	Event extraction using behaviors of sentiment signals and burst structure in social media. Knowl. Inf. Syst. Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2013	A	`conf`	Exploiting side information in distance dependent Chinese restaurant processes for data clustering. ICME Cheng Li, Dinh Q. Phung, Santu Rana, Svetha Venkatesh
2013	A*	`conf`	Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes. PerCom Nguyen Cong Thuong, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh
2013	—	`conf`	Factorial Multi-Task Learning : A Bayesian Nonparametric Approach. ICML (3) Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2013	—	`conf`	Interactive browsing system for anomaly video surveillance. ISSNIP Tien-Vu Nguyen, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh
2013	—	`conf`	Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine. PAKDD (1) Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2013	C	`conf`	Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine. ACML Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2013	A	`conf`	Learning sparse latent representation and distance metric for image retrieval. ICME Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2013	J	`jnl`	Regularized nonnegative shared subspace learning. Data Min. Knowl. Discov. Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2013	A	`conf`	Sparse Subspace Clustering via Group Sparse Coding. SDM Duc-Son Pham, Dinh Q. Phung, Budhaditya Saha, Svetha Venkatesh
2013	—	`conf`	Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes. PAKDD (2) Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2013	A*	`conf`	TOBY: early intervention in autism through technology. CHI Svetha Venkatesh, Dinh Q. Phung, Thi V. Duong, Stewart Greenhill, Brett Adams
2013	—	`conf`	Thurstonian Boltzmann Machines: Learning from Multiple Inequalities. ICML (2) Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2013	—	`conf`	Topic Model Kernel: An Empirical Study towards Probabilistically Reduced Features for Classification. ICONIP (2) Tien-Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh
2012	A	`conf`	A Sentiment-Aware Approach to Community Formation in Social Media. ICWSM Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2012	A*	`conf`	A Sequential Decision Approach to Ordinal Preferences in Recommender Systems. AAAI Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2012	J	`jnl`	A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning CoRR Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2012	A	`conf`	A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning. UAI Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2012	B	`conf`	A nonparametric Bayesian Poisson gamma model for count data. ICPR Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
2012	C	`conf`	Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis. ACML Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2012	C	`conf`	Embedded Restricted Boltzmann Machines for fusion of mixed data types and applications in social measurements analysis. FUSION Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2012	—	`conf`	Funniest thing i've seen since [href=//flic.kr/p/KGEGB]: shifting perspectives from multimedia artefacts to utterances. SAM@MM Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2012	A*	`conf`	Improved subspace clustering via exploitation of spatial constraints. CVPR Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh
2012	—	`conf`	Large-scale statistical modeling of motion patterns: a Bayesian nonparametric approach. ICVGIP Santu Rana, Dinh Q. Phung, Sonny Pham, Svetha Venkatesh
2012	A	`conf`	Learning Boltzmann Distance Metric for Face Recognition. ICME Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2012	C	`conf`	Learning From Ordered Sets and Applications in Collaborative Ranking. ACML Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2012	B	`conf`	Multi-modal abnormality detection in video with unknown data segmentation. ICPR Tien-Vu Nguyen, Dinh Q. Phung, Santu Rana, Duc-Son Pham, Svetha Venkatesh
2012	J	`jnl`	Ordinal Boltzmann Machines for Collaborative Filtering CoRR Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
2012	J	`jnl`	Pervasive multimedia for autism intervention. Pervasive Mob. Comput. Svetha Venkatesh, Stewart Greenhill, Dinh Q. Phung, Brett Adams, Thi V. Duong
2012	A*	`conf`	Sparse Subspace Representation for Spectral Document Clustering. ICDM Budhaditya Saha, Dinh Q. Phung, Duc-Son Pham, Svetha Venkatesh
2011	—	`conf`	A Bayesian Framework for Learning Shared and Individual Subspaces from Multiple Data Sources. PAKDD (1) Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2011	—	`conf`	A context-sensitive device to help people with autism cope with anxiety. CHI Extended Abstracts Marziya Mohammedali, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2011	A*	`conf`	Cognitive intervention in autism using multimedia stimulus. ACM Multimedia Svetha Venkatesh, Stewart Greenhill, Dinh Q. Phung, Brett Adams
2011	A*	`conf`	Detection of Cross-Channel Anomalies from Multiple Data Channels. ICDM Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh
2011	—	`conf`	Emotional Reactions to Real-World Events in Social Networks. PAKDD Workshops Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2011	A*	`conf`	Eventscapes: visualizing events over time with emotive facets. ACM Multimedia Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2011	C	`conf`	Mixed-Variate Restricted Boltzmann Machines. ACML Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2011	B	`conf`	Prediction of Age, Sentiment, and Connectivity from Social Media Text. WISE Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2011	A	`conf`	Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering. SDM Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
2011	A	`conf`	Towards Discovery of Influence and Personality Traits through Social Link Prediction. ICWSM Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2010	—	`conf`	Classification and Pattern Discovery of Mood in Weblogs. PAKDD (2) Thin Nguyen, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh
2010	J	`jnl`	Discovery of latent subcommunities in a blog's readership. ACM Trans. Web Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2010	J	`jnl`	Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data CoRR Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh
2010	—	`conf`	Hyper-community detection in the blogosphere. WSM@MM Thin Nguyen, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh
2010	A*	`conf`	Nonnegative shared subspace learning and its application to social media retrieval. KDD Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh
2010	J	`jnl`	Probabilistic Models over Ordered Partitions with Application in Learning to Rank CoRR Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
2009	J	`jnl`	Efficient duration and hierarchical modeling for human activity recognition. Artif. Intell. Thi V. Duong, Dinh Q. Phung, Hung Bui, Svetha Venkatesh
2009	A*	`conf`	Flickr hypergroups. ACM Multimedia Radu Andrei Negoescu, Brett Adams, Dinh Q. Phung, Svetha Venkatesh, Daniel Gatica-Perez
2009	A*	`conf`	High Accuracy Context Recovery using Clustering Mechanisms. PerCom Dinh Q. Phung, Brett Adams, Kha Tran, Svetha Venkatesh, Mohan Kumar
2009	A	`conf`	Ordinal Boltzmann Machines for Collaborative Filtering. UAI Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
2009	—	`conf`	Social reader: following social networks in the wilds of the blogosphere. WSM@MM Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2009	J	`jnl`	Unsupervised context detection using wireless signals. Pervasive Mob. Comput. Dinh Q. Phung, Brett Adams, Svetha Venkatesh, Mohan Kumar
2008	J	`jnl`	"You Tube and I Find" - Personalizing Multimedia Content Access. Proc. IEEE Svetha Venkatesh, Brett Adams, Dinh Q. Phung, Chitra Dorai, Robert G. Farrell, Lalitha Agnihotri, Nevenka Dimitrova
2008	—	`conf`	Computable social patterns from sparse sensor data. LocWeb Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2008	B	`conf`	Constrained Sequence Classification for Lexical Disambiguation. PRICAI Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
2008	—	`conf`	Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data. NIPS Tran The Truyen, Dinh Q. Phung, Hung Bui, Svetha Venkatesh
2008	Misc	`conf`	Indoor Location Prediction Using Multiple Wireless Received Signal Strengths. AusDM Kha Tran, Dinh Q. Phung, Brett Adams, Svetha Venkatesh
2008	B	`conf`	Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition. PRICAI Tran The Truyen, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh
2008	J	`jnl`	Sensing and using social context. ACM Trans. Multim. Comput. Commun. Appl. Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2008	A*	`conf`	The Hidden Permutation Model and Location-Based Activity Recognition. AAAI Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh, Hai Phan
2007	Misc	`conf`	Preference Networks: Probabilistic Models for Recommendation Systems. AusDM Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
2006	—	`conf`	A probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment. ICPR (3) Dung T. Tran, Dinh Q. Phung
2006	—	`conf`	AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition. CVPR (2) Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
2006	A*	`conf`	Extraction of social context and application to personal multimedia exploration. ACM Multimedia Brett Adams, Dinh Q. Phung, Svetha Venkatesh
2006	—	`conf`	Human Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model. ICPR (3) Thi V. Duong, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh
2005	—	`conf`	Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model. CVPR (1) Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh
2005	—	`conf`	Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models. CVPR (2) Nam Thanh Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Bui
2005	A*	`conf`	Topic transition detection using hierarchical hidden Markov and semi-Markov models. ACM Multimedia Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hung Hai Bui
2004	B	`conf`	Automatically learning structural units in educational videos with the hierarchical hidden markov models. ICIP Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
2004	—	`conf`	Content Structure Discovery in Educational Videos Using Shared Structures in the Hierarchical Hidden Markov Models. SSPR/SPR Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh
2004	A*	`conf`	Learning Hierarchical Hidden Markov Models with General State Hierarchy. AAAI Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh
2003	A*	`conf`	Hierarchical topical segmentation in instructional films based on cinematic expressive functions. ACM Multimedia Dinh Q. Phung, Svetha Venkatesh, Chitra Dorai
2002	A*	`conf`	High level segmentation of instructional videos based on content density. ACM Multimedia Dinh Q. Phung, Svetha Venkatesh, Chitra Dorai