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ORCIDDinh Q. Phung
Dinh Quoc Phung – Dinh Phung 0001
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- affiliation: Monash University, Melbourne, Victoria, Australia
- affiliation: Deakin University, Center of Pattern Recognition and Data Analytics, Australia
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Journal Articles
- 2024
[j68]Michael Fu, Chakkrit Tantithamthavorn
, Trung Le, Yuki Kume, Van Nguyen, Dinh Q. Phung, John C. Grundy:
AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities. Empir. Softw. Eng. 29(1): 4 (2024)- [j67]Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai:
Class Enhancement Losses With Pseudo Labels for Open-Vocabulary Semantic Segmentation. IEEE Trans. Multim. 26: 8442-8453 (2024) - [j66]Michael Fu, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung, Trung Le:
Vision Transformer Inspired Automated Vulnerability Repair. ACM Trans. Softw. Eng. Methodol. 33(3): 78:1-78:29 (2024) - [j65]Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Dinh Q. Phung:
Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection. ACM Trans. Softw. Eng. Methodol. 33(6): 162 (2024) - 2023
- [j64]Hung Bui, Nguyen Minh Le, Dat Quoc Nguyen, Linh Pham, Dinh Q. Phung:
Building and Nurturing AI Development in Vietnam. Commun. ACM 66(7): 75-76 (2023) - [j63]Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai:
Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing 555: 126605 (2023) - [j62]Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung:
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. Trans. Mach. Learn. Res. 2023 (2023) - [j61]Michael Fu, Van Nguyen, Chakkrit Kla Tantithamthavorn, Trung Le, Dinh Q. Phung:
VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types. IEEE Trans. Software Eng. 49(10): 4550-4565 (2023) - 2022
- [j60]Trung Le, Khanh Nguyen, Dinh Q. Phung:
Improving kernel online learning with a snapshot memory. Mach. Learn. 111(3): 997-1018 (2022) - [j59]Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Geoffrey I. Webb, Dinh Phung:
Robust Variational Learning for Multiclass Kernel Models With Stein Refinement. IEEE Trans. Knowl. Data Eng. 34(9): 4425-4438 (2022) - 2021
- [j58]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. 22: 145:1-145:43 (2021) - 2020
- [j57]Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Hung Nguyen, Duc Thanh Nguyen, John Yearwood, Dinh Quoc Phung, Svetha Venkatesh, Helen Christensen:
Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices. Future Gener. Comput. Syst. 110: 620-628 (2020) - [j56]Wenhe Liu, Xiaojun Chang, Ling Chen, Dinh Phung, Xiaoqin Zhang, Yi Yang, Alexander G. Hauptmann:
Pair-based Uncertainty and Diversity Promoting Early Active Learning for Person Re-identification. ACM Trans. Intell. Syst. Technol. 11(2): 21:1-21:15 (2020) - 2019
- [j55]Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
GoGP: scalable geometric-based Gaussian process for online regression. Knowl. Inf. Syst. 60(1): 197-226 (2019) - [j54]Dai Quoc Nguyen, Dat Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A convolutional neural network-based model for knowledge base completion and its application to search personalization. Semantic Web 10(5): 947-960 (2019) - 2018
- [j53]Dang Nguyen, Wei Luo, Svetha Venkatesh, Dinh Q. Phung:
Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding. J. Medical Syst. 42(5): 94:1-94:13 (2018) - [j52]Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Academia versus social media: A psycho-linguistic analysis. J. Comput. Sci. 25: 228-237 (2018) - [j51]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh:
Discovering topic structures of a temporally evolving document corpus. Knowl. Inf. Syst. 55(3): 599-632 (2018) - [j50]Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh:
LTARM: A novel temporal association rule mining method to understand toxicities in a routine cancer treatment. Knowl. Based Syst. 161: 313-328 (2018) - [j49]Ba-Ngu Vo, Nhan Dam, Dinh Q. Phung, Quang N. Tran, Ba-Tuong Vo:
Model-based learning for point pattern data. Pattern Recognit. 84: 136-151 (2018) - 2017
- [j48]Truyen Tran, Dinh Quoc Phung, Hung Bui, Svetha Venkatesh:
Hierarchical semi-Markov conditional random fields for deep recursive sequential data. Artif. Intell. 246: 53-85 (2017) - [j47]Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Duc Thanh Nguyen, John Yearwood, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
Kernel-based features for predicting population health indices from geocoded social media data. Decis. Support Syst. 102: 22-31 (2017) - [j46]Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Latent sentiment topic modelling and nonparametric discovery of online mental health-related communities. Int. J. Data Sci. Anal. 4(3): 209-231 (2017) - [j45]Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
Estimation of the prevalence of adverse drug reactions from social media. Int. J. Medical Informatics 102: 130-137 (2017) - [j44]Viet Huynh, Dinh Q. Phung:
Streaming clustering with Bayesian nonparametric models. Neurocomputing 258: 52-62 (2017) - [j43]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Predicting healthcare trajectories from medical records: A deep learning approach. J. Biomed. Informatics 69: 218-229 (2017) - [j42]Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Approximation Vector Machines for Large-scale Online Learning. J. Mach. Learn. Res. 18: 111:1-111:55 (2017) - [j41]Pratibha Vellanki, Thi V. Duong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung:
Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data. Knowl. Inf. Syst. 51(1): 127-157 (2017) - [j40]Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions. Knowl. Inf. Syst. 53(1): 179-206 (2017) - [j39]Thin Nguyen, Bridianne O'Dea, Mark E. Larsen, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
Using linguistic and topic analysis to classify sub-groups of online depression communities. Multim. Tools Appl. 76(8): 10653-10676 (2017) - [j38]Nguyen Cong Thuong, Vu Nguyen, Flora D. Salim, Duc Viet Le, Dinh Q. Phung:
A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process. Pervasive Mob. Comput. 38: 396-417 (2017) - [j37]Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare. IEEE J. Biomed. Health Informatics 21(4): 1182-1191 (2017) - 2016
- [j36]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Graph-induced restricted Boltzmann machines for document modeling. Inf. Sci. 328: 60-75 (2016) - [j35]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Collaborative filtering via sparse Markov random fields. Inf. Sci. 369: 221-237 (2016) - [j34]Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Stabilizing l1-norm prediction models by supervised feature grouping. J. Biomed. Informatics 59: 149-168 (2016) - [j33]Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
Multiple task transfer learning with small sample sizes. Knowl. Inf. Syst. 46(2): 315-342 (2016) - [j32]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach. Knowl. Inf. Syst. 47(1): 157-188 (2016) - [j31]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Data clustering using side information dependent Chinese restaurant processes. Knowl. Inf. Syst. 47(2): 463-488 (2016) - [j30]Sunil Gupta, Santu Rana, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
A new transfer learning framework with application to model-agnostic multi-task learning. Knowl. Inf. Syst. 49(3): 933-973 (2016) - [j29]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records. Knowl. Based Syst. 99: 168-182 (2016) - [j28]Hang Li, Dinh Q. Phung, Tru H. Cao, Tu Bao Ho, Zhi-Hua Zhou:
Introduction: special issue of selected papers from ACML 2014. Mach. Learn. 103(2): 137-139 (2016) - [j27]Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
Modelling multilevel data in multimedia: A hierarchical factor analysis approach. Multim. Tools Appl. 75(9): 4933-4955 (2016) - [j26]Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung:
Nonparametric discovery of movement patterns from accelerometer signals. Pattern Recognit. Lett. 70: 52-58 (2016) - [j25]Budhaditya Saha, Thin Nguyen, Dinh Q. Phung, Svetha Venkatesh:
A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression. IEEE J. Biomed. Health Informatics 20(4): 1008-1015 (2016) - 2015
- [j24]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Tree-based iterated local search for Markov random fields with applications in image analysis. J. Heuristics 21(1): 25-45 (2015) - [j23]Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso. J. Biomed. Informatics 53: 277-290 (2015) - [j22]Truyen Tran, Tu Dinh Nguyen, Dinh Q. Phung, Svetha Venkatesh:
Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM). J. Biomed. Informatics 54: 96-105 (2015) - [j21]Truyen Tran, Dinh Q. Phung, Wei Luo, Svetha Venkatesh:
Stabilized sparse ordinal regression for medical risk stratification. Knowl. Inf. Syst. 43(3): 555-582 (2015) - [j20]Xin Zhang, Duc-Son Pham, Svetha Venkatesh, Wanquan Liu, Dinh Q. Phung:
Mixed-norm sparse representation for multi view face recognition. Pattern Recognit. 48(9): 2935-2946 (2015) - [j19]Santu Rana, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
A predictive framework for modeling healthcare data with evolving clinical interventions. Stat. Anal. Data Min. 8(3): 162-182 (2015) - [j18]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh, Terry Caelli:
Using Twitter to learn about the autism community. Soc. Netw. Anal. Min. 5(1): 22:1-22:17 (2015) - [j17]Thin Nguyen, Thi V. Duong, Svetha Venkatesh, Dinh Q. Phung:
Autism Blogs: Expressed Emotion, Language Styles and Concerns in Personal and Community Settings. IEEE Trans. Affect. Comput. 6(3): 312-323 (2015) - [j16]Shivapratap Gopakumar, Truyen Tran, Tu Dinh Nguyen, Dinh Q. Phung, Svetha Venkatesh:
Stabilizing High-Dimensional Prediction Models Using Feature Graphs. IEEE J. Biomed. Health Informatics 19(3): 1044-1052 (2015) - 2014
- [j15]Truyen Tran, Wei Luo, Dinh Q. Phung, Sunil Gupta, Santu Rana, Richard Kennedy, Ann Larkins, Svetha Venkatesh:
A framework for feature extraction from hospital medical data with applications in risk prediction. BMC Bioinform. 15: 6596 (2014) - [j14]Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Mood sensing from social media texts and its applications. Knowl. Inf. Syst. 39(3): 667-702 (2014) - [j13]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Social reader: towards browsing the social web. Multim. Tools Appl. 69(3): 951-990 (2014) - [j12]Thin Nguyen, Dinh Q. Phung, Bo Dao, Svetha Venkatesh, Michael Berk:
Affective and Content Analysis of Online Depression Communities. IEEE Trans. Affect. Comput. 5(3): 217-226 (2014) - [j11]Ba-Ngu Vo, Ba-Tuong Vo, Dinh Q. Phung:
Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter. IEEE Trans. Signal Process. 62(24): 6554-6567 (2014) - 2013
- [j10]Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Regularized nonnegative shared subspace learning. Data Min. Knowl. Discov. 26(1): 57-97 (2013) - [j9]Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
Detection of cross-channel anomalies. Knowl. Inf. Syst. 35(1): 33-59 (2013) - [j8]Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Event extraction using behaviors of sentiment signals and burst structure in social media. Knowl. Inf. Syst. 37(2): 279-304 (2013) - [j7]Dinh Q. Phung, Sunil Kumar Gupta, Thin Nguyen, Svetha Venkatesh:
Connectivity, Online Social Capital, and Mood: A Bayesian Nonparametric Analysis. IEEE Trans. Multim. 15(6): 1316-1325 (2013) - 2012
- [j6]Svetha Venkatesh, Stewart Greenhill, Dinh Q. Phung, Brett Adams, Thi V. Duong:
Pervasive multimedia for autism intervention. Pervasive Mob. Comput. 8(6): 863-882 (2012) - 2010
- [j5]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Discovery of latent subcommunities in a blog's readership. ACM Trans. Web 4(3): 12:1-12:30 (2010) - 2009
- [j4]Thi V. Duong, Dinh Q. Phung, Hung Bui, Svetha Venkatesh:
Efficient duration and hierarchical modeling for human activity recognition. Artif. Intell. 173(7-8): 830-856 (2009) - [j3]Dinh Q. Phung, Brett Adams, Svetha Venkatesh, Mohan Kumar:
Unsupervised context detection using wireless signals. Pervasive Mob. Comput. 5(6): 714-733 (2009) - 2008
- [j2]Svetha Venkatesh, Brett Adams, Dinh Q. Phung, Chitra Dorai, Robert G. Farrell, Lalitha Agnihotri, Nevenka Dimitrova:
"You Tube and I Find" - Personalizing Multimedia Content Access. Proc. IEEE 96(4): 697-711 (2008) - [j1]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Sensing and using social context. ACM Trans. Multim. Comput. Commun. Appl. 5(2): 11:1-11:27 (2008)
Conference and Workshop Papers
- 2024
- [c244]Thi Nguyen, Linhao Luo, Fatemeh Shiri, Dinh Phung, Yuan-Fang Li, Thuy-Trang Vu, Gholamreza Haffari:
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs. ACL (Findings) 2024: 2862-2883 - [c243]Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Phung, Lizhen Qu:
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. ICLR 2024 - [c242]Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung:
Optimal Transport for Structure Learning Under Missing Data. ICML 2024 - [c241]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung:
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport. ICML 2024 - [c240]Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do:
Frequency Attention for Knowledge Distillation. WACV 2024: 2266-2275 - 2023
- [c239]Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung:
Global-Local Regularization Via Distributional Robustness. AISTATS 2023: 7644-7664 - [c238]Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung, Gholamreza Haffari:
Systematic Assessment of Factual Knowledge in Large Language Models. EMNLP (Findings) 2023: 13272-13286 - [c237]Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen:
Two-View Graph Neural Networks for Knowledge Graph Completion. ESWC 2023: 262-278 - [c236]Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho:
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks. ICASSP 2023: 1-5 - [c235]Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Phung:
An Additive Instance-Wise Approach to Multi-class Model Interpretation. ICLR 2023 - [c234]Son Duy Dao, Dat Huynh, He Zhao, Dinh Phung, Jianfei Cai:
Open-Vocabulary Multi-label Image Classification with Pretrained Vision-Language Model. ICME 2023: 2135-2140 - [c233]Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung:
Vector Quantized Wasserstein Auto-Encoder. ICML 2023: 35223-35242 - [c232]Thien Hai Nguyen, Thinh Pham, Khoi Minh Le, Manh Luong, Nguyen Luong Tran, Hieu Man, Dang Minh Nguyen, Tuan Anh Luu, Thien Huu Nguyen, Hung Bui, Dinh Phung, Dat Quoc Nguyen:
A Vietnamese Spelling Correction System. IUI Companion 2023: 158-161 - [c231]Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung:
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. KDD 2023: 2211-2222 - [c230]Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung:
Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation. MICCAI (1) 2023: 183-194 - [c229]Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung:
Optimal Transport Model Distributional Robustness. NeurIPS 2023 - [c228]Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le:
Flat Seeking Bayesian Neural Networks. NeurIPS 2023 - [c227]Van Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do:
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. NeurIPS 2023 - [c226]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung:
Adversarial local distribution regularization for knowledge distillation. WACV 2023: 4670-4679 - 2022
- [c225]Thuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza Haffari:
Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out Training. ACL (Findings) 2022: 582-588 - [c224]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung:
Particle-based Adversarial Local Distribution Regularization. AISTATS 2022: 5212-5224 - [c223]Tam Le, Truyen Nguyen, Dinh Phung, Viet Anh Nguyen:
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. AISTATS 2022: 9844-9868 - [c222]Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Hung Tran, Dinh Q. Phung:
On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds. AISTATS 2022: 11438-11460 - [c221]Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung:
Bridging Global Context Interactions for High-Fidelity Image Completion. CVPR 2022: 11502-11512 - [c220]Linh Vu, Raphaël C.-W. Phan, Lim Wern Han, Dinh Phung:
Improved speech emotion recognition based on music-related audio features. EUSIPCO 2022: 120-124 - [c219]Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung:
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR 2022 - [c218]Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho:
On Transportation of Mini-batches: A Hierarchical Approach. ICML 2022: 16622-16655 - [c217]Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Phung:
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection. ICSE-Companion 2022: 178-182 - [c216]Tuan-Duy H. Nguyen, Duy Phung, Duy Tran-Cong Nguyen, Hieu Minh Tran, Manh Luong, Tin Duy Vo, Hung Hai Bui, Dinh Q. Phung, Dat Quoc Nguyen:
A Vietnamese-English Neural Machine Translation System. INTERSPEECH 2022: 5543-5544 - [c215]Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung:
MED-TEX: Transfer and Explain Knowledge with Less Data from Pretrained Medical Imaging Models. ISBI 2022: 1-4 - [c214]Tin Duy Vo, Manh Luong, Duong Minh Le, Hieu Tran, Nhan Do, Tuan-Duy H. Nguyen, Thien Nguyen, Hung Bui, Dat Quoc Nguyen, Dinh Q. Phung:
Vietnamese Speech-based Question Answering over Car Manuals. IUI Companion 2022: 117-119 - [c213]Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung:
Stochastic Multiple Target Sampling Gradient Descent. NeurIPS 2022 - [c212]Chuanxia Zheng, Tung-Long Vuong, Jianfei Cai, Dinh Phung:
MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. NeurIPS 2022 - [c211]Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, Dinh Q. Phung:
VulRepair: a T5-based automated software vulnerability repair. ESEC/SIGSOFT FSE 2022: 935-947 - [c210]Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung:
Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. UAI 2022: 1519-1529 - [c209]Thuy-Trang Vu, Shahram Khadivi, Xuanli He, Dinh Phung, Gholamreza Haffari:
Can Domains Be Transferred across Languages in Multi-Domain Multilingual Neural Machine Translation? WMT 2022: 381-396 - [c208]Dai Quoc Nguyen, Vinh Tong, Dinh Q. Phung, Dat Quoc Nguyen:
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction. WSDM 2022: 1589-1592 - [c207]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Q. Phung:
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. WWW (Companion Volume) 2022: 189-192 - [c206]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Universal Graph Transformer Self-Attention Networks. WWW (Companion Volume) 2022: 193-196 - 2021
- [c205]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. AAAI 2021: 6831-6839 - [c204]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Quaternion Graph Neural Networks. ACML 2021: 236-251 - [c203]Thuy-Trang Vu, Xuanli He, Dinh Q. Phung, Gholamreza Haffari:
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection. EMNLP (1) 2021: 3335-3346 - [c202]Van-Anh Nguyen, Tuan Nguyen, Trung Le, Quan Hung Tran, Dinh Phung:
STEM: An approach to Multi-source Domain Adaptation with Guarantees. ICCV 2021: 9332-9343 - [c201]He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine:
Neural Topic Model via Optimal Transport. ICLR 2021 - [c200]Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung:
LAMDA: Label Matching Deep Domain Adaptation. ICML 2021: 6043-6054 - [c199]Tuan Nguyen, Trung Le, Nhan Dam, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung:
TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport. IJCAI 2021: 2862-2868 - [c198]Viet Huynh, Dinh Q. Phung, He Zhao:
Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI 2021: 4450-4457 - [c197]He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine:
Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI 2021: 4713-4720 - [c196]Van Nguyen, Trung Le, Olivier Y. de Vel, Paul Montague, John Grundy, Dinh Phung:
Information-theoretic Source Code Vulnerability Highlighting. IJCNN 2021: 1-8 - [c195]Manh-Ha Bui, Toan Tran, Anh Tran, Dinh Q. Phung:
Exploiting Domain-Specific Features to Enhance Domain Generalization. NeurIPS 2021: 21189-21201 - [c194]Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. NeurIPS 2021: 27720-27733 - [c193]Tuan Nguyen, Trung Le, He Zhao, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung:
Most: multi-source domain adaptation via optimal transport for student-teacher learning. UAI 2021: 225-235 - 2020
- [c192]Dai Quoc Nguyen, Tuan Nguyen, Dinh Phung:
A Relational Memory-based Embedding Model for Triple Classification and Search Personalization. ACL 2020: 3429-3435 - [c191]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou:
Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS 2020: 1684-1694 - [c190]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung:
A Capsule Network-based Model for Learning Node Embeddings. CIKM 2020: 3313-3316 - [c189]Quan Hung Tran, Nhan Dam, Tuan Manh Lai, Franck Dernoncourt, Trung Le, Nham Le, Dinh Phung:
Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering. COLING 2020: 5205-5210 - [c188]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Q. Phung:
Improving Adversarial Robustness by Enforcing Local and Global Compactness. ECCV (27) 2020: 209-223 - [c187]Thuy-Trang Vu, Dinh Phung, Gholamreza Haffari:
Effective Unsupervised Domain Adaptation with Adversarially Trained Language Models. EMNLP (1) 2020: 6163-6173 - [c186]Quan Hoang, Trung Le, Dinh Phung:
Parameterized Rate-Distortion Stochastic Encoder. ICML 2020: 4293-4303 - [c185]Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung:
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. ICPR 2020: 8922-8928 - [c184]Nhan Dam, Trung Le, Viet Huynh, Dinh Phung:
Stein Variational Gradient Descent with Variance Reduction. IJCNN 2020: 1-8 - [c183]Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung:
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation. IJCNN 2020: 1-8 - [c182]Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier Y. de Vel, Paul Montague, Dinh Phung:
Code Pointer Network for Binary Function Scope Identification. IJCNN 2020: 1-7 - [c181]Viet Huynh, He Zhao, Dinh Phung:
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling. NeurIPS 2020 - [c180]Tuan Nguyen, Trung Le, Khanh Nguyen, Olivier Y. de Vel, Paul Montague, John C. Grundy, Dinh Phung:
Deep Cost-Sensitive Kernel Machine for Binary Software Vulnerability Detection. PAKDD (2) 2020: 164-177 - [c179]Van Nguyen, Trung Le, Olivier Y. de Vel, Paul Montague, John C. Grundy, Dinh Phung:
Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection. PAKDD (1) 2020: 699-711 - [c178]Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier Y. de Vel, Paul Montague, John C. Grundy, Dinh Phung:
Code Action Network for Binary Function Scope Identification. PAKDD (1) 2020: 712-725 - [c177]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-attention Network Based Node Embedding Model. ECML/PKDD (3) 2020: 364-377 - 2019
- [c176]Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung:
Robust Anomaly Detection in Videos Using Multilevel Representations. AAAI 2019: 5216-5223 - [c175]Thuy-Trang Vu, Ming Liu, Dinh Phung, Gholamreza Haffari:
Learning How to Active Learn by Dreaming. ACL (1) 2019: 4091-4101 - [c174]Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan:
Probabilistic Multilevel Clustering via Composite Transportation Distance. AISTATS 2019: 3149-3157 - [c173]Tue Le, Tuan Nguyen, Trung Le, Dinh Q. Phung, Paul Montague, Olivier Y. de Vel, Lizhen Qu:
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection. ICLR (Poster) 2019 - [c172]Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung:
Three-Player Wasserstein GAN via Amortised Duality. IJCAI 2019: 2202-2208 - [c171]Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung:
Learning Generative Adversarial Networks from Multiple Data Sources. IJCAI 2019: 2823-2829 - [c170]Van Nguyen, Trung Le, Tue Le, Khanh Nguyen, Olivier Y. DeVel, Paul Montague, Lizhen Qu, Dinh Q. Phung:
Deep Domain Adaptation for Vulnerable Code Function Identification. IJCNN 2019: 1-8 - [c169]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung:
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. NAACL-HLT (1) 2019: 2180-2189 - 2018
- [c168]Khanh Nguyen, Nhan Dam, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung:
Clustering Induced Kernel Learning. ACML 2018: 129-144 - [c167]Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung:
Batch Normalized Deep Boltzmann Machines. ACML 2018: 359-374 - [c166]Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung:
MGAN: Training Generative Adversarial Nets with Multiple Generators. ICLR (Poster) 2018 - [c165]Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung:
Bayesian Multi-Hyperplane Machine for Pattern Recognition. ICPR 2018: 609-614 - [c164]Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung:
Geometric Enclosing Networks. IJCAI 2018: 2355-2361 - [c163]Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, Geoffrey I. Webb:
Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data. KDD 2018: 2003-2011 - [c162]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung:
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. NAACL-HLT (2) 2018: 327-333 - [c161]Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint. ECML/PKDD (2) 2018: 569-584 - [c160]Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Learning Graph Representation via Frequent Subgraphs. SDM 2018: 306-314 - [c159]Hung Nguyen, Van Nguyen, Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Duc Thanh Nguyen, Trung Le, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
Jointly Predicting Affective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web. WISE (2) 2018: 100-110 - 2017
- [c158]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Column Networks for Collective Classification. AAAI 2017: 2485-2491 - [c157]Hung Nguyen, Sarah J. Maclagan, Tu Dinh Nguyen, Thin Nguyen, Paul Flemons, Kylie Andrews, Euan G. Ritchie, Dinh Q. Phung:
Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring. DSAA 2017: 40-49 - [c156]Nhan Dam, Dinh Q. Phung, Ba-Ngu Vo, Viet Huynh:
Forward-Backward Smoothing for Hidden Markov Models of Point Pattern Data. DSAA 2017: 252-261 - [c155]Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
GoGP: Fast Online Regression with Gaussian Processes. ICDM 2017: 257-266 - [c154]Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung:
Multilevel Clustering via Wasserstein Means. ICML 2017: 1501-1509 - [c153]Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung:
Large-scale Online Kernel Learning with Random Feature Reparameterization. IJCAI 2017: 2543-2549 - [c152]Vu Nguyen, Dinh Q. Phung, Trung Le, Hung Bui:
Discriminative Bayesian Nonparametric Clustering. IJCAI 2017: 2550-2556 - [c151]Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung:
Dual Discriminator Generative Adversarial Nets. NIPS 2017: 2670-2680 - [c150]Hung Vu, Tu Dinh Nguyen, Anthony Travers, Svetha Venkatesh, Dinh Q. Phung:
Energy-Based Localized Anomaly Detection in Video Surveillance. PAKDD (1) 2017: 641-653 - [c149]Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le:
Supervised Restricted Boltzmann Machines. UAI 2017 - [c148]Thin Nguyen, Nguyen Hung, Svetha Venkatesh, Dinh Q. Phung:
Estimating Support Scores of Autism Communities in Large-Scale Web Information Systems. WISE (1) 2017: 347-355 - [c147]Thin Nguyen, Duc Thanh Nguyen, Mark E. Larsen, Bridianne O'Dea, John Yearwood, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
Prediction of Population Health Indices from Social Media using Kernel-based Textual and Temporal Features. WWW (Companion Volume) 2017: 99-107 - 2016
- [c146]Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Multiple Kernel Learning with Data Augmentation. ACML 2016: 49-64 - [c145]Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Textual Cues for Online Depression in Community and Personal Settings. ADMA 2016: 19-34 - [c144]Kien Do, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Outlier Detection on Mixed-Type Data: An Energy-Based Approach. ADMA 2016: 111-125 - [c143]Shivapratap Gopakumar, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Stabilizing Linear Prediction Models Using Autoencoder. ADMA 2016: 651-663 - [c142]Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Nonparametric Budgeted Stochastic Gradient Descent. AISTATS 2016: 654-572 - [c141]Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh:
Exceptional Contrast Set Mining: Moving Beyond the Deluge of the Obvious. Australasian Conference on Artificial Intelligence 2016: 455-468 - [c140]Thanh-Binh Nguyen, Vu Nguyen, Nguyen Cong Thuong, Svetha Venkatesh, Mohan Kumar, Dinh Q. Phung:
Learning Multifaceted Latent Activities from Heterogeneous Mobile Data. DSAA 2016: 389-398 - [c139]Adham Beykikhoshk, Dinh Q. Phung, Ognjen Arandjelovic, Svetha Venkatesh:
Analysing the History of Autism Spectrum Disorder Using Topic Models. DSAA 2016: 762-771 - [c138]Pratibha Vellanki, Thi V. Duong, Dinh Q. Phung, Svetha Venkatesh:
Data Mining of Intervention for Children with Autism Spectrum Disorder. eHealth 360° 2016: 376-383 - [c137]Vu Nguyen, Tu Dinh Nguyen, Trung Le, Svetha Venkatesh, Dinh Q. Phung:
One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems. ICDM 2016: 1113-1118 - [c136]Shivapratap Gopakumar, Truyen Tran, Wei Luo, Dinh Q. Phung, Svetha Venkatesh:
Forecasting Patient Outflow from Wards having No Real-Time Clinical Data. ICHI 2016: 177-183 - [c135]Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Discovering latent affective dynamics among individuals in online mental health-related communities. ICME 2016: 1-6 - [c134]Tu Dinh Nguyen, Vu Nguyen, Trung Le, Dinh Q. Phung:
Distributed data augmented support vector machine on Spark. ICPR 2016: 498-503 - [c133]Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model. ICPR 2016: 537-542 - [c132]Ba-Ngu Vo, Nhat-Quang Tran, Dinh Q. Phung, Ba-Tuong Vo:
Model-based classification and novelty detection for point pattern data. ICPR 2016: 2622-2627 - [c131]Nhat-Quang Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo:
Clustering for point pattern data. ICPR 2016: 3174-3179 - [c130]Iman Kamkar, Sunil Gupta, Cheng Li, Dinh Q. Phung, Svetha Venkatesh:
Stable clinical prediction using graph support vector machines. ICPR 2016: 3332-3337 - [c129]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Faster training of very deep networks via p-norm gates. ICPR 2016: 3542-3547 - [c128]Thanh-Binh Nguyen, Vu Nguyen, Svetha Venkatesh, Dinh Q. Phung:
MCNC: Multi-Channel Nonparametric Clustering from heterogeneous data. ICPR 2016: 3633-3638 - [c127]Truyen Tran, Wei Luo, Dinh Q. Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh:
Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data. MLHC 2016: 164-177 - [c126]Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Dual Space Gradient Descent for Online Learning. NIPS 2016: 4583-4591 - [c125]Pratibha Vellanki, Stewart Greenhill, Thi V. Duong, Dinh Q. Phung, Svetha Venkatesh, Jayashree Godwin, Krishnaveni Achary, Blessin Varkey:
Computer assisted autism interventions for India. OZCHI 2016: 618-622 - [c124]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Neural Choice by Elimination via Highway Networks. PAKDD Workshops 2016: 15-25 - [c123]Khanh Nguyen, Trung Le, Vu Nguyen, Dinh Q. Phung:
Sparse Adaptive Multi-hyperplane Machine. PAKDD (1) 2016: 27-39 - [c122]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
DeepCare: A Deep Dynamic Memory Model for Predictive Medicine. PAKDD (2) 2016: 30-41 - [c121]Thanh-Binh Nguyen, Vu Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes. PAKDD Workshops 2016: 128-140 - [c120]Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely, Dinh Q. Phung:
Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. PAKDD (1) 2016: 152-164 - [c119]Nguyen Cong Thuong, Vu Nguyen, Flora D. Salim, Dinh Q. Phung:
SECC: Simultaneous extraction of context and community from pervasive signals. PerCom 2016: 1-9 - [c118]Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Effect of social capital on emotion, language style and latent topics in online depression community. RIVF 2016: 61-66 - [c117]Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui:
Scalable Nonparametric Bayesian Multilevel Clustering. UAI 2016 - [c116]Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Budgeted Semi-supervised Support Vector Machine . UAI 2016 - [c115]Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Large-Scale Stylistic Analysis of Formality in Academia and Social Media. WISE (2) 2016: 137-145 - [c114]Thin Nguyen, Ron Borland, John Yearwood, Hua-Hie Yong, Svetha Venkatesh, Dinh Q. Phung:
Discriminative Cues for Different Stages of Smoking Cessation in Online Community. WISE (2) 2016: 146-153 - 2015
- [c113]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Tensor-Variate Restricted Boltzmann Machines. AAAI 2015: 2887-2893 - [c112]Viet Huynh, Dinh Q. Phung, Svetha Venkatesh:
Streaming Variational Inference for Dirichlet Process Mixtures. ACML 2015: 237-252 - [c111]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh:
Overcoming Data Scarcity of Twitter: Using Tweets as Bootstrap with Application to Autism-Related Topic Content Analysis. ASONAM 2015: 1354-1361 - [c110]Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Stable Feature Selection with Support Vector Machines. Australasian Conference on Artificial Intelligence 2015: 298-308 - [c109]Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh:
Understanding Toxicities and Complications of Cancer Treatment: A Data Mining Approach. Australasian Conference on Artificial Intelligence 2015: 431-443 - [c108]Dinh Q. Phung, Dat Tran, Wanli Ma, Tien Pham:
Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. CISIS-ICEUTE 2015: 145-155 - [c107]Dinh Q. Phung, Dat Tran, Wanli Ma, Tien Pham:
Conditional Entropy Approach to Multichannel EEG-Based Person Identification. CISIS-ICEUTE 2015: 157-165 - [c106]Xin Zhang, Dinh Q. Phung, Svetha Venkatesh, Duc-Son Pham, Wanquan Liu:
Multi-View Subspace Clustering for Face Images. DICTA 2015: 1-7 - [c105]Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Nonparametric discovery of online mental health-related communities. DSAA 2015: 1-10 - [c104]Iman Kamkar, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Exploiting feature relationships towards stable feature selection. DSAA 2015: 1-10 - [c103]Tien Pham, Wanli Ma, Dat Tran, Duc Su Tran, Dinh Q. Phung:
A study on the stability of EEG signals for user authentication. NER 2015: 122-125 - [c102]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. PAKDD (2) 2015: 92-105 - [c101]Trung Le, Dinh Q. Phung, Khanh Nguyen, Svetha Venkatesh:
Fast One-Class Support Vector Machine for Novelty Detection. PAKDD (2) 2015: 189-200 - [c100]Pratibha Vellanki, Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh:
Learning Entry Profiles of Children with Autism from Multivariate Treatment Information Using Restricted Boltzmann Machines. PAKDD Workshops 2015: 245-257 - [c99]Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning. PAKDD (1) 2015: 303-316 - [c98]Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
A Bayesian Nonparametric Approach to Multilevel Regression. PAKDD (1) 2015: 330-342 - [c97]Shivapratap Gopakumar, Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records. PAKDD (2) 2015: 331-343 - [c96]Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui:
Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) 2015: 343-354 - [c95]Adham Beykikhoshk, Ognjen Arandjelovic, Svetha Venkatesh, Dinh Q. Phung:
Hierarchical Dirichlet Process for Tracking Complex Topical Structure Evolution and Its Application to Autism Research Literature. PAKDD (1) 2015: 550-562 - [c94]Sunil Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. SDM 2015: 703-711 - [c93]Xin Zhang, Duc-Son Pham, Dinh Q. Phung, Wanquan Liu, Budhaditya Saha, Svetha Venkatesh:
Visual Object Clustering via Mixed-Norm Regularization. WACV 2015: 1030-1037 - [c92]Thin Nguyen, Bridianne O'Dea, Mark E. Larsen, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
Differentiating Sub-groups of Online Depression-Related Communities Using Textual Cues. WISE (2) 2015: 216-224 - 2014
- [c91]Dinh Q. Phung, Hang Li:
Preface. ACML 2014 - [c90]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh, Terry Caelli:
Data-mining twitter and the autism spectrum disorder: A Pilot study. ASONAM 2014: 349-356 - [c89]Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Analysis of circadian rhythms from online communities of individuals with affective disorders. DSAA 2014: 463-469 - [c88]Thanh-Binh Nguyen, Wei Luo, Terry Caelli, Svetha Venkatesh, Dinh Q. Phung:
Individualized arrhythmia detection with ECG signals from wearable devices. DSAA 2014: 570-576 - [c87]Dinh Q. Phung, Dat Tran, Wanli Ma, Phuoc Nguyen, Tien Pham:
Using Shannon Entropy as EEG Signal Feature for Fast Person Identification. ESANN 2014 - [c86]Dinh Q. Phung, Ba-Ngu Vo:
A random finite set model for data clustering. FUSION 2014: 1-8 - [c85]Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Bui:
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. ICML 2014: 288-296 - [c84]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. ICPR 2014: 1307-1312 - [c83]Pratibha Vellanki, Thi V. Duong, Svetha Venkatesh, Dinh Q. Phung:
Nonparametric Discovery of Learning Patterns and Autism Subgroups from Therapeutic Data. ICPR 2014: 1828-1833 - [c82]Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung:
A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data. ICPR 2014: 2017-2022 - [c81]Dinh Q. Phung, Dat Tran, Wanli Ma, Phuoc Nguyen, Tien Pham:
Investigating the impacts of epilepsy on EEG-based person identification systems. IJCNN 2014: 3644-3648 - [c80]Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung:
Multi-factor EEG-based user authentication. IJCNN 2014: 4029-4034 - [c79]Thanh-Binh Nguyen, Nguyen Cong Thuong, Wei Luo, Svetha Venkatesh, Dinh Q. Phung:
Unsupervised inference of significant locations from WiFi data for understanding human dynamics. MUM 2014: 232-235 - [c78]Santu Rana, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Intervention-Driven Predictive Framework for Modeling Healthcare Data. PAKDD (1) 2014: 497-508 - [c77]Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung:
Fixed-lag particle filter for continuous context discovery using Indian Buffet Process. PerCom 2014: 20-28 - [c76]Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions. SDM 2014: 235-243 - [c75]Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung:
EEG-Based User Authentication Using Artifacts. SOCO-CISIS-ICEUTE 2014: 343-353 - [c74]Thin Nguyen, Dinh Q. Phung, Wei Luo, Truyen Tran, Svetha Venkatesh:
iPoll: Automatic Polling Using Online Search. WISE (1) 2014: 266-275 - [c73]Bo Dao, Thin Nguyen, Dinh Q. Phung, Svetha Venkatesh:
Effect of Mood, Social Connectivity and Age in Online Depression Community via Topic and Linguistic Analysis. WISE (1) 2014: 398-407 - [c72]Thin Nguyen, Thi V. Duong, Dinh Q. Phung, Svetha Venkatesh:
Affective, Linguistic and Topic Patterns in Online Autism Communities. WISE (2) 2014: 474-488 - 2013
- [c71]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine. ACML 2013: 133-148 - [c70]Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung:
EEG-Based User Authentication in Multilevel Security Systems. ADMA (2) 2013: 513-523 - [c69]Svetha Venkatesh, Dinh Q. Phung, Thi V. Duong, Stewart Greenhill, Brett Adams:
TOBY: early intervention in autism through technology. CHI 2013: 3187-3196 - [c68]Cheng Li, Dinh Q. Phung, Santu Rana, Svetha Venkatesh:
Exploiting side information in distance dependent Chinese restaurant processes for data clustering. ICME 2013: 1-6 - [c67]Thin Nguyen, Dinh Q. Phung, Svetha Venkatesh:
Analysis of psycholinguistic processes and topics in online autism communities. ICME 2013: 1-6 - [c66]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning sparse latent representation and distance metric for image retrieval. ICME 2013: 1-6 - [c65]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Thurstonian Boltzmann Machines: Learning from Multiple Inequalities. ICML (2) 2013: 46-54 - [c64]Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Factorial Multi-Task Learning : A Bayesian Nonparametric Approach. ICML (3) 2013: 657-665 - [c63]Tien-Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh:
Topic Model Kernel: An Empirical Study towards Probabilistically Reduced Features for Classification. ICONIP (2) 2013: 124-131 - [c62]Tien Pham, Wanli Ma, Dat Tran, Phuoc Nguyen, Dinh Q. Phung:
A Study on the Feasibility of Using EEG Signals for Authentication Purpose. ICONIP (2) 2013: 562-569 - [c61]Phuoc Nguyen, Dat Tran, Tan Vo, Xu Huang, Wanli Ma, Dinh Q. Phung:
EEG-Based Age and Gender Recognition Using Tensor Decomposition and Speech Features. ICONIP (2) 2013: 632-639 - [c60]Thin Nguyen, Bo Dao, Dinh Quoc Phung, Svetha Venkatesh, Michael Berk:
Online Social Capital: Mood, Topical and Psycholinguistic Analysis. ICWSM 2013 - [c59]Tien-Vu Nguyen, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh:
Interactive browsing system for anomaly video surveillance. ISSNIP 2013: 384-389 - [c58]Truyen Tran, Dinh Q. Phung, Wei Luo, Richard Harvey, Michael Berk, Svetha Venkatesh:
An integrated framework for suicide risk prediction. KDD 2013: 1410-1418 - [c57]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine. PAKDD (1) 2013: 123-135 - [c56]Budhaditya Saha, Duc-Son Pham, Dinh Q. Phung, Svetha Venkatesh:
Clustering Patient Medical Records via Sparse Subspace Representation. PAKDD (2) 2013: 123-134 - [c55]Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes. PAKDD (2) 2013: 546-557 - [c54]Nguyen Cong Thuong, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh:
Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes. PerCom 2013: 47-55 - [c53]Duc-Son Pham, Dinh Q. Phung, Budhaditya Saha, Svetha Venkatesh:
Sparse Subspace Clustering via Group Sparse Coding. SDM 2013: 130-138 - 2012
- [c52]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
A Sequential Decision Approach to Ordinal Preferences in Recommender Systems. AAAI 2012: 676-682 - [c51]Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
Improved subspace clustering via exploitation of spatial constraints. CVPR 2012: 550-557 - [c50]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Embedded Restricted Boltzmann Machines for fusion of mixed data types and applications in social measurements analysis. FUSION 2012: 1814-1821 - [c49]Budhaditya Saha, Dinh Q. Phung, Duc-Son Pham, Svetha Venkatesh:
Sparse Subspace Representation for Spectral Document Clustering. ICDM 2012: 1092-1097 - [c48]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning Boltzmann Distance Metric for Face Recognition. ICME 2012: 218-223 - [c47]Tien-Vu Nguyen, Dinh Q. Phung, Santu Rana, Duc-Son Pham, Svetha Venkatesh:
Multi-modal abnormality detection in video with unknown data segmentation. ICPR 2012: 1322-1325 - [c46]Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
A nonparametric Bayesian Poisson gamma model for count data. ICPR 2012: 1815-1818 - [c45]Santu Rana, Dinh Q. Phung, Sonny Pham, Svetha Venkatesh:
Large-scale statistical modeling of motion patterns: a Bayesian nonparametric approach. ICVGIP 2012: 7 - [c44]Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
A Sentiment-Aware Approach to Community Formation in Social Media. ICWSM 2012 - [c43]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Funniest thing i've seen since [href=//flic.kr/p/KGEGB]: shifting perspectives from multimedia artefacts to utterances. SAM@MM 2012: 57-60 - [c42]Sunil Kumar Gupta, Dinh Quoc Phung, Svetha Venkatesh:
A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources. SDM 2012: 200-211 - [c41]Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning. UAI 2012: 316-325 - [c40]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis. ACML 2012: 411-426 - [c39]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning From Ordered Sets and Applications in Collaborative Ranking. ACML 2012: 427-442 - 2011
- [c38]Marziya Mohammedali, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
A context-sensitive device to help people with autism cope with anxiety. CHI Extended Abstracts 2011: 1201-1206 - [c37]Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
Detection of Cross-Channel Anomalies from Multiple Data Channels. ICDM 2011: 527-536 - [c36]Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Towards Discovery of Influence and Personality Traits through Social Link Prediction. ICWSM 2011 - [c35]Svetha Venkatesh, Stewart Greenhill, Dinh Q. Phung, Brett Adams:
Cognitive intervention in autism using multimedia stimulus. ACM Multimedia 2011: 769-770 - [c34]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Eventscapes: visualizing events over time with emotive facets. ACM Multimedia 2011: 1477-1480 - [c33]Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Emotional Reactions to Real-World Events in Social Networks. PAKDD Workshops 2011: 53-64 - [c32]Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
A Bayesian Framework for Learning Shared and Individual Subspaces from Multiple Data Sources. PAKDD (1) 2011: 136-147 - [c31]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering. SDM 2011: 426-437 - [c30]Thin Nguyen, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Prediction of Age, Sentiment, and Connectivity from Social Media Text. WISE 2011: 227-240 - [c29]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Mixed-Variate Restricted Boltzmann Machines. ACML 2011: 213-229 - 2010
- [c28]Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh:
Nonnegative shared subspace learning and its application to social media retrieval. KDD 2010: 1169-1178 - [c27]Thin Nguyen, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh:
Hyper-community detection in the blogosphere. WSM@MM 2010: 21-26 - [c26]Thin Nguyen, Dinh Q. Phung, Brett Adams, Truyen Tran, Svetha Venkatesh:
Classification and Pattern Discovery of Mood in Weblogs. PAKDD (2) 2010: 283-290 - 2009
- [c25]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Social reader: following social networks in the wilds of the blogosphere. WSM@MM 2009: 73-80 - [c24]Radu Andrei Negoescu, Brett Adams, Dinh Q. Phung, Svetha Venkatesh, Daniel Gatica-Perez:
Flickr hypergroups. ACM Multimedia 2009: 813-816 - [c23]Dinh Q. Phung, Brett Adams, Kha Tran, Svetha Venkatesh, Mohan Kumar:
High Accuracy Context Recovery using Clustering Mechanisms. PerCom 2009: 1-9 - [c22]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
Ordinal Boltzmann Machines for Collaborative Filtering. UAI 2009: 548-556 - 2008
- [c21]Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh, Hai Phan:
The Hidden Permutation Model and Location-Based Activity Recognition. AAAI 2008: 1345-1350 - [c20]Kha Tran, Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Indoor Location Prediction Using Multiple Wireless Received Signal Strengths. AusDM 2008: 187-192 - [c19]Tran The Truyen, Dinh Q. Phung, Hung Bui, Svetha Venkatesh:
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data. NIPS 2008: 1657-1664 - [c18]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
Constrained Sequence Classification for Lexical Disambiguation. PRICAI 2008: 430-441 - [c17]Tran The Truyen, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh:
Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition. PRICAI 2008: 903-912 - [c16]Dinh Q. Phung, Brett Adams, Svetha Venkatesh:
Computable social patterns from sparse sensor data. LocWeb 2008: 69-72 - 2007
- [c15]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
Preference Networks: Probabilistic Models for Recommendation Systems. AusDM 2007: 195-202 - 2006
- [c14]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition. CVPR (2) 2006: 1686-1693 - [c13]Dung T. Tran, Dinh Q. Phung:
A probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment. ICPR (3) 2006: 168-172 - [c12]Thi V. Duong, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh:
Human Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model. ICPR (3) 2006: 202-207 - [c11]Brett Adams, Dinh Q. Phung, Svetha Venkatesh:
Extraction of social context and application to personal multimedia exploration. ACM Multimedia 2006: 987-996 - 2005
- [c10]Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh:
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model. CVPR (1) 2005: 838-845 - [c9]Nam Thanh Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Bui:
Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models. CVPR (2) 2005: 955-960 - [c8]Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hung Hai Bui:
Topic transition detection using hierarchical hidden Markov and semi-Markov models. ACM Multimedia 2005: 11-20 - 2004
- [c7]Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh:
Learning Hierarchical Hidden Markov Models with General State Hierarchy. AAAI 2004: 324-329 - [c6]Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
Automatically learning structural units in educational videos with the hierarchical hidden markov models. ICIP 2004: 1605-1608 - [c5]Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh:
Content Structure Discovery in Educational Videos Using Shared Structures in the Hierarchical Hidden Markov Models. SSPR/SPR 2004: 1155-1163 - 2003
- [c4]Dinh Quoc Phung, Svetha Venkatesh, Chitra Dorai:
On the extraction of thematic and dramatic functions of content in educational videos. ICME 2003: 449-452 - [c3]Dinh Q. Phung, Svetha Venkatesh, Chitra Dorai:
Hierarchical topical segmentation in instructional films based on cinematic expressive functions. ACM Multimedia 2003: 287-290 - 2002
- [c2]Dinh Quoc Phung, Chitra Dorai, Svetha Venkatesh:
Narrative Structure Analysis with Education and Training Videos for E-Learning. ICPR (2) 2002: 835- - [c1]Dinh Q. Phung, Svetha Venkatesh, Chitra Dorai:
High level segmentation of instructional videos based on content density. ACM Multimedia 2002: 295-298
Editorship
- 2018
- [e4]Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi:
Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part I. Lecture Notes in Computer Science 10937, Springer 2018, ISBN 978-3-319-93033-6 [contents] - [e3]Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi:
Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part II. Lecture Notes in Computer Science 10938, Springer 2018, ISBN 978-3-319-93036-7 [contents] - [e2]Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi:
Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part III. Lecture Notes in Computer Science 10939, Springer 2018, ISBN 978-3-319-93039-8 [contents] - 2014
- [e1]Dinh Q. Phung, Hang Li:
Proceedings of the Sixth Asian Conference on Machine Learning, ACML 2014, Nha Trang City, Vietnam, November 26-28, 2014. JMLR Workshop and Conference Proceedings 39, JMLR.org 2014 [contents]
Informal and Other Publications
- 2024
- [i131]Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung:
A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation. CoRR abs/2401.15952 (2024) - [i130]Minh-Vuong Nguyen, Linhao Luo, Fatemeh Shiri, Dinh Phung, Yuan-Fang Li, Thuy-Trang Vu, Gholamreza Haffari:
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs. CoRR abs/2402.11199 (2024) - [i129]Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung:
Optimal Transport for Structure Learning Under Missing Data. CoRR abs/2402.15255 (2024) - [i128]Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do:
Frequency Attention for Knowledge Distillation. CoRR abs/2403.05894 (2024) - [i127]Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung:
Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts. CoRR abs/2403.12326 (2024) - [i126]Anh Bui, Vy Vo, Tung Pham, Dinh Q. Phung, Trung Le:
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers. CoRR abs/2403.13204 (2024) - [i125]Minh-Tuan Tran, Trung Le, Xuan-May Thi Le, Mehrtash Harandi, Dinh Phung:
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning. CoRR abs/2403.14101 (2024) - [i124]Cheng Zhang, Qianyi Wu, Camilo Cruz Gambardella, Xiaoshui Huang, Dinh Q. Phung, Wanli Ouyang, Jianfei Cai:
Taming Stable Diffusion for Text to 360{\deg} Panorama Image Generation. CoRR abs/2404.07949 (2024) - [i123]Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Q. Phung, Lizhen Qu:
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. CoRR abs/2405.10084 (2024) - [i122]Shangyu Chen, Zizheng Pan, Jianfei Cai, Dinh Q. Phung:
PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction. CoRR abs/2406.05641 (2024) - [i121]Van-Anh Nguyen, Quyen Tran, Tuan Truong, Thanh-Toan Do, Dinh Quoc Phung, Trung Le:
Agnostic Sharpness-Aware Minimization. CoRR abs/2406.07107 (2024) - [i120]Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du:
LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. CoRR abs/2406.09008 (2024) - [i119]Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Q. Phung, Gustavo Carneiro, Thanh-Toan Do:
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. CoRR abs/2407.02721 (2024) - [i118]Cuong Pham, Hoang Anh Dung, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do:
MetaAug: Meta-Data Augmentation for Post-Training Quantization. CoRR abs/2407.14726 (2024) - [i117]Khanh Doan, Long Tung Vuong, Tuan Nguyen, Anh Tuan Bui, Quyen Tran, Thanh-Toan Do, Dinh Phung, Trung Le:
Connective Viewpoints of Signal-to-Noise Diffusion Models. CoRR abs/2408.04221 (2024) - 2023
- [i116]Son Duy Dao, Hengcan Shi, Dinh Q. Phung, Jianfei Cai:
Class Enhancement Losses with Pseudo Labels for Zero-shot Semantic Segmentation. CoRR abs/2301.07336 (2023) - [i115]Van-Anh Nguyen, Long Tung Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le:
Flat Seeking Bayesian Neural Networks. CoRR abs/2302.02713 (2023) - [i114]Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung:
Vector Quantized Wasserstein Auto-Encoder. CoRR abs/2302.05917 (2023) - [i113]Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Q. Phung:
Hyperbolic Geometry in Computer Vision: A Survey. CoRR abs/2304.10764 (2023) - [i112]Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Q. Phung:
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. CoRR abs/2304.13229 (2023) - [i111]Thuy-Trang Vu, Shahram Khadivi, Dinh Q. Phung, Gholamreza Haffari:
Active Continual Learning: Labelling Queries in a Sequence of Tasks. CoRR abs/2305.03923 (2023) - [i110]Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Q. Phung, Trung Le:
Sharpness & Shift-Aware Self-Supervised Learning. CoRR abs/2305.10252 (2023) - [i109]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Q. Phung:
Learning Directed Graphical Models with Optimal Transport. CoRR abs/2305.15927 (2023) - [i108]Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Yuki Kume, Van Nguyen, Dinh Phung, John C. Grundy:
AIBugHunter: A Practical Tool for Predicting, Classifying and Repairing Software Vulnerabilities. CoRR abs/2305.16615 (2023) - [i107]Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung:
Optimal Transport Model Distributional Robustness. CoRR abs/2306.04178 (2023) - [i106]Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Q. Phung:
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities. CoRR abs/2306.06109 (2023) - [i105]Xiaohao Yang, He Zhao, Dinh Phung, Lan Du:
Towards Generalising Neural Topical Representations. CoRR abs/2307.12564 (2023) - [i104]Tuan Truong, Hoang-Phi Nguyen, Tung Pham, Minh-Tuan Tran, Mehrtash Harandi, Dinh Phung, Trung Le:
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization. CoRR abs/2309.17215 (2023) - [i103]Minh-Tuan Tran, Trung Le, Xuan-May Thi Le, Mehrtash Harandi, Quan Hung Tran, Dinh Q. Phung:
Unleash Data Generation for Efficient and Effective Data-free Knowledge Distillation. CoRR abs/2310.00258 (2023) - [i102]Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung:
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation. CoRR abs/2310.01176 (2023) - [i101]Linhao Luo, Thuy-Trang Vu, Dinh Q. Phung, Gholamreza Haffari:
Systematic Assessment of Factual Knowledge in Large Language Models. CoRR abs/2310.11638 (2023) - [i100]Dat Quoc Nguyen, Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, Nhung Nguyen, Thien Huu Nguyen, Dinh Q. Phung, Hung Hai Bui:
PhoGPT: Generative Pre-training for Vietnamese. CoRR abs/2311.02945 (2023) - [i99]Ngoc N. Tran, Lam Tran, Hoang Phan, Anh Tuan Bui, Tung Pham, Toan Tran, Dinh Q. Phung, Trung Le:
Robust Contrastive Learning With Theory Guarantee. CoRR abs/2311.09671 (2023) - [i98]Quyen Tran, Lam Tran, Khoat Than, Toan Tran, Dinh Q. Phung, Trung Le:
KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All. CoRR abs/2311.15414 (2023) - [i97]Khanh Doan, Quyen Tran, Tuan Nguyen, Dinh Q. Phung, Trung Le:
Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay. CoRR abs/2312.06710 (2023) - 2022
- [i96]Tam Le, Truyen Nguyen, Dinh Q. Phung, Viet Anh Nguyen:
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. CoRR abs/2202.10723 (2022) - [i95]Tuan-Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung:
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR abs/2202.13437 (2022) - [i94]Hoang Phan, Trung Le, Trung Phung, Tuan-Anh Bui, Nhat Ho, Dinh Q. Phung:
Global-Local Regularization Via Distributional Robustness. CoRR abs/2203.00553 (2022) - [i93]Chuanxia Zheng, Guoxian Song, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung, Linjie Luo:
High-Quality Pluralistic Image Completion via Code Shared VQGAN. CoRR abs/2204.01931 (2022) - [i92]Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung:
Stochastic Multiple Target Sampling Gradient Descent. CoRR abs/2206.01934 (2022) - [i91]Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Q. Phung:
An Additive Instance-Wise Approach to Multi-class Model Interpretation. CoRR abs/2207.03113 (2022) - [i90]Chuanxia Zheng, Long Tung Vuong, Jianfei Cai, Dinh Q. Phung:
MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. CoRR abs/2209.09002 (2022) - [i89]Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Hung Nguyen, Dinh Q. Phung:
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle. CoRR abs/2209.10406 (2022) - [i88]Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John C. Grundy, Hung Nguyen, Seyit Camtepe, Paul Quirk, Dinh Q. Phung:
An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability. CoRR abs/2209.10414 (2022) - [i87]Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung:
Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. CoRR abs/2209.13446 (2022) - [i86]Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong, Thanh-Toan Do, Quan Hung Tran, Dinh Q. Phung, Trung Le:
Vision Transformer Visualization: What Neurons Tell and How Neurons Behave? CoRR abs/2210.07646 (2022) - [i85]Thuy-Trang Vu, Shahram Khadivi, Xuanli He, Dinh Q. Phung, Gholamreza Haffari:
Can Domains Be Transferred Across Languages in Multi-Domain Multilingual Neural Machine Translation? CoRR abs/2210.11628 (2022) - [i84]Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Q. Phung, Trung Le:
Improving Multi-task Learning via Seeking Task-based Flat Regions. CoRR abs/2211.13723 (2022) - [i83]Quyen Tran, Hoang Phan, Khoat Than, Dinh Q. Phung, Trung Le:
Continual Learning with Optimal Transport based Mixture Model. CoRR abs/2211.16780 (2022) - [i82]Ngoc N. Tran, Anh Tuan Bui, Dinh Q. Phung, Trung Le:
Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance. CoRR abs/2212.03069 (2022) - 2021
- [i81]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung:
Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning. CoRR abs/2101.10027 (2021) - [i80]Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le:
BoMb-OT: On Batch of Mini-batches Optimal Transport. CoRR abs/2102.05912 (2021) - [i79]He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine:
Topic Modelling Meets Deep Neural Networks: A Survey. CoRR abs/2103.00498 (2021) - [i78]Dai Quoc Nguyen, Vinh Tong, Dinh Phung, Dat Quoc Nguyen:
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction. CoRR abs/2104.07396 (2021) - [i77]Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung:
Improved and Efficient Text Adversarial Attacks using Target Information. CoRR abs/2104.13484 (2021) - [i76]Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung:
Text Generation with Deep Variational GAN. CoRR abs/2104.13488 (2021) - [i75]Son Duy Dao, Ethan Zhao, Dinh Phung, Jianfei Cai:
Multi-Label Image Classification with Contrastive Learning. CoRR abs/2107.11626 (2021) - [i74]Jing Liu, Bohan Zhuang, Mingkui Tan, Xu Liu, Dinh Phung, Yuanqing Li, Jianfei Cai:
Elastic Architecture Search for Diverse Tasks with Different Resources. CoRR abs/2108.01224 (2021) - [i73]Thuy-Trang Vu, Xuanli He, Dinh Q. Phung, Gholamreza Haffari:
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection. CoRR abs/2109.04292 (2021) - [i72]Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Q. Phung:
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection. CoRR abs/2110.07317 (2021) - [i71]Manh-Ha Bui, Toan Tran, Anh Tuan Tran, Dinh Phung:
Exploiting Domain-Specific Features to Enhance Domain Generalization. CoRR abs/2110.09410 (2021) - [i70]Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung:
On Label Shift in Domain Adaptation via Wasserstein Distance. CoRR abs/2110.15520 (2021) - [i69]Dang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho:
Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment. CoRR abs/2110.15538 (2021) - [i68]Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. CoRR abs/2111.13822 (2021) - [i67]Vinh Tong, Dai Quoc Nguyen, Dinh Q. Phung, Dat Quoc Nguyen:
Two-view Graph Neural Networks for Knowledge Graph Completion. CoRR abs/2112.09231 (2021) - 2020
- [i66]Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung:
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation. CoRR abs/2004.07534 (2020) - [i65]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-Attention Network based Node Embedding Model. CoRR abs/2006.12100 (2020) - [i64]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung:
Improving Adversarial Robustness by Enforcing Local and Global Compactness. CoRR abs/2007.05123 (2020) - [i63]Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung:
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models. CoRR abs/2008.02593 (2020) - [i62]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
Quaternion Graph Neural Networks. CoRR abs/2008.05089 (2020) - [i61]He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine:
Neural Sinkhorn Topic Model. CoRR abs/2008.13537 (2020) - [i60]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung:
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. CoRR abs/2009.09612 (2020) - [i59]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Phung:
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. CoRR abs/2009.12517 (2020) - [i58]Thuy-Trang Vu, Dinh Phung, Gholamreza Haffari:
Effective Unsupervised Domain Adaptation with Adversarially Trained Language Models. CoRR abs/2010.01739 (2020) - [i57]He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images. CoRR abs/2010.06131 (2020) - [i56]Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung:
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. CoRR abs/2010.06812 (2020) - [i55]Quan Hung Tran, Nhan Dam, Tuan Manh Lai, Franck Dernoncourt, Trung Le, Nham Le, Dinh Phung:
Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering. CoRR abs/2011.03096 (2020) - 2019
- [i54]Trung Le, Dinh Q. Phung:
When Can Neural Networks Learn Connected Decision Regions? CoRR abs/1901.08710 (2019) - [i53]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Relational Memory-based Knowledge Graph Embedding. CoRR abs/1907.06080 (2019) - [i52]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On Efficient Multilevel Clustering via Wasserstein Distances. CoRR abs/1909.08787 (2019) - [i51]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
Unsupervised Universal Self-Attention Network for Graph Classification. CoRR abs/1909.11855 (2019) - [i50]He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions. CoRR abs/1910.01329 (2019) - [i49]Tam Le, Viet Huynh, Nhat Ho, Dinh Q. Phung, Makoto Yamada:
On Scalable Variant of Wasserstein Barycenter. CoRR abs/1910.04483 (2019) - [i48]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung:
A Capsule Network-based Model for Learning Node Embeddings. CoRR abs/1911.04822 (2019) - 2018
- [i47]Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung:
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models. CoRR abs/1805.01090 (2018) - [i46]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung:
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. CoRR abs/1808.04122 (2018) - [i45]Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan:
Probabilistic Multilevel Clustering via Composite Transportation Distance. CoRR abs/1810.11911 (2018) - [i44]Trung Le, Khanh Nguyen, Dinh Q. Phung:
Theoretical Perspective of Deep Domain Adaptation. CoRR abs/1811.06199 (2018) - 2017
- [i43]Ba-Ngu Vo, Quang N. Tran, Dinh Q. Phung, Ba-Tuong Vo:
Model-based Classification and Novelty Detection For Point Pattern Data. CoRR abs/1701.08473 (2017) - [i42]Quang N. Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo:
Clustering For Point Pattern Data. CoRR abs/1702.02262 (2017) - [i41]Ba-Ngu Vo, Dinh Q. Phung, Quang N. Tran, Ba-Tuong Vo:
Model-Based Multiple Instance Learning. CoRR abs/1703.02155 (2017) - [i40]Quang N. Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo, Nguyen Cong Thuong:
Multiple Instance Learning with the Optimal Sub-Pattern Assignment Metric. CoRR abs/1703.08933 (2017) - [i39]Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung:
Multi-Generator Generative Adversarial Nets. CoRR abs/1708.02556 (2017) - [i38]Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung:
Geometric Enclosing Networks. CoRR abs/1708.04733 (2017) - [i37]Hung Vu, Dinh Q. Phung, Tu Dinh Nguyen, Anthony Trevors, Svetha Venkatesh:
Energy-based Models for Video Anomaly Detection. CoRR abs/1708.05211 (2017) - [i36]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Statistical Latent Space Approach for Mixed Data Modelling and Applications. CoRR abs/1708.05594 (2017) - [i35]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization. CoRR abs/1708.05603 (2017) - [i34]Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung:
Dual Discriminator Generative Adversarial Nets. CoRR abs/1709.03831 (2017) - [i33]Trung Le, Khanh Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Analogical-based Bayesian Optimization. CoRR abs/1709.06390 (2017) - [i32]Trung Le, Tu Dinh Nguyen, Dinh Q. Phung:
KGAN: How to Break The Minimax Game in GAN. CoRR abs/1711.01744 (2017) - [i31]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung:
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. CoRR abs/1712.02121 (2017) - 2016
- [i30]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
DeepCare: A Deep Dynamic Memory Model for Predictive Medicine. CoRR abs/1602.00357 (2016) - [i29]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Collaborative filtering via sparse Markov random fields. CoRR abs/1602.02842 (2016) - [i28]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Choice by Elimination via Deep Neural Networks. CoRR abs/1602.05285 (2016) - [i27]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning deep representation of multityped objects and tasks. CoRR abs/1603.01359 (2016) - [i26]Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Approximation Vector Machines for Large-scale Online Learning. CoRR abs/1604.06518 (2016) - [i25]Nguyen Cong Thuong, Truyen Tran, Shivapratap Gopakumar, Dinh Q. Phung, Svetha Venkatesh:
An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments. CoRR abs/1605.01116 (2016) - [i24]Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Q. Phung:
Scalable Support Vector Machine for Semi-supervised Learning. CoRR abs/1606.06793 (2016) - [i23]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Faster Training of Very Deep Networks Via p-Norm Gates. CoRR abs/1608.03639 (2016) - [i22]Kien Do, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Outlier Detection on Mixed-Type Data: An Energy-based Approach. CoRR abs/1608.04830 (2016) - [i21]Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Column Networks for Collective Classification. CoRR abs/1609.04508 (2016) - [i20]Dang Nguyen, Wei Luo, Dinh Q. Phung, Svetha Venkatesh:
Control Matching via Discharge Code Sequences. CoRR abs/1612.01812 (2016) - 2015
- [i19]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh:
Hierarchical Dirichlet process for tracking complex topical structure evolution and its application to autism research literature. CoRR abs/1502.02233 (2015) - [i18]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh, Terry Caelli:
Using Twitter to learn about the autism community. CoRR abs/1506.00246 (2015) - [i17]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh:
Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis. CoRR abs/1507.02973 (2015) - [i16]Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Q. Phung, Svetha Venkatesh:
Discovering topic structures of a temporally evolving document corpus. CoRR abs/1512.08008 (2015) - 2014
- [i15]Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui:
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR abs/1401.1974 (2014) - [i14]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Tree-based iterated local search for Markov random fields with applications in image analysis. CoRR abs/1407.5754 (2014) - [i13]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
Preference Networks: Probabilistic Models for Recommendation Systems. CoRR abs/1407.5764 (2014) - [i12]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning Rank Functionals: An Empirical Study. CoRR abs/1407.6089 (2014) - [i11]Shivapratap Gopakumar, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Stabilizing Sparse Cox Model using Clinical Structures in Electronic Medical Records. CoRR abs/1407.6094 (2014) - [i10]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning Structured Outputs from Partial Labels using Forest Ensemble. CoRR abs/1407.6432 (2014) - [i9]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning From Ordered Sets and Applications in Collaborative Ranking. CoRR abs/1408.0043 (2014) - [i8]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis. CoRR abs/1408.0047 (2014) - [i7]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Thurstonian Boltzmann Machines: Learning from Multiple Inequalities. CoRR abs/1408.0055 (2014) - [i6]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Mixed-Variate Restricted Boltzmann Machines. CoRR abs/1408.1160 (2014) - [i5]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
MCMC for Hierarchical Semi-Markov Conditional Random Fields. CoRR abs/1408.1162 (2014) - 2012
- [i4]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
Ordinal Boltzmann Machines for Collaborative Filtering. CoRR abs/1205.2611 (2012) - [i3]Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning. CoRR abs/1210.4855 (2012) - 2010
- [i2]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh:
Probabilistic Models over Ordered Partitions with Application in Learning to Rank. CoRR abs/1009.1690 (2010) - [i1]Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh:
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data. CoRR abs/1009.2009 (2010)
Coauthor Index
[j68] [j66] [j65] [j62] [j61] [j60] [j59] [j55] [j42] [c242] [c241] [c240] [c239] [c235] [c233] [c231] [c230] [c229] [c228] [c227] [c226] [c224] [c222] [c219] [c218] [c217] [c213] [c211] [c210] [c205] [c202] [c201] [c200] [c199] [c196] [c194] [c193] [c189] [c188] [c186] [c185] [c184] [c183] [c182] [c180] [c179] [c178] [c176] [c173] [c172] [c171] [c170] [c168] [c167] [c166] [c165] [c164] [c163] [c159] [c155] [c153] [c152] [c151] [c149] [c146] [c142] [c137] [c134] [c126] [c123] [c116] [c101] [i131] [i129] [i128] [i127] [i126] [i125] [i121] [i119] [i118] [i117] [i115] [i114] [i113] [i112] [i110] [i109] [i108] [i107] [i106] [i104] [i103] [i102] [i99] [i98] [i97] [i95] [i94] [i92] [i91] [i89] [i88] [i87] [i86] [i84] [i83] [i82] [i81] [i80] [i77] [i76] [i72] [i70] [i68] [i66] [i64] [i61] [i60] [i57] [i56] [i55] [i54] [i50] [i44] [i39] [i38] [i34] [i33] [i32] [i26] [i24]
[j59] [j55] [j54] [j42] [j36] [j22] [j16] [c207] [c206] [c204] [c190] [c177] [c176] [c172] [c171] [c169] [c168] [c167] [c166] [c165] [c164] [c163] [c162] [c161] [c160] [c157] [c155] [c153] [c151] [c150] [c149] [c146] [c142] [c137] [c134] [c126] [c116] [c113] [c97] [c71] [c66] [c57] [i65] [i62] [i59] [i53] [i51] [i48] [i47] [i46] [i39] [i38] [i37] [i36] [i35] [i34] [i33] [i32] [i31] [i26]
Vu Nguyen 0001
aka: Tien-Vu Nguyen
aka: Tien-Vu Nguyen
Duc-Son Pham 0001
aka: Sonny Pham
aka: Sonny Pham
Chakkrit Tantithamthavorn
aka: Chakkrit Kla Tantithamthavorn
aka: Chakkrit Kla Tantithamthavorn
Truyen Tran 0001
aka: Tran The Truyen
aka: Tran The Truyen
[j48] [j43] [j36] [j35] [j32] [j24] [j22] [j21] [j16] [j15] [c158] [c144] [c143] [c136] [c129] [c127] [c124] [c122] [c113] [c97] [c74] [c71] [c66] [c65] [c58] [c57] [c52] [c50] [c48] [c40] [c39] [c31] [c29] [c28] [c27] [c26] [c22] [c19] [c18] [c17] [c15] [c14] [i36] [i35] [i30] [i29] [i28] [i27] [i25] [i23] [i22] [i21] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i2] [i1]
Olivier Y. de Vel
aka: Olivier Y. DeVel
aka: Olivier Y. DeVel
[j57] [j53] [j52] [j51] [j50] [j48] [j47] [j46] [j45] [j43] [j41] [j40] [j39] [j37] [j36] [j35] [j34] [j33] [j32] [j31] [j30] [j29] [j27] [j26] [j25] [j24] [j23] [j22] [j21] [j20] [j19] [j18] [j17] [j16] [j15] [j14] [j13] [j12] [j10] [j9] [j8] [j7] [j6] [j5] [j4] [j3] [j2] [j1] [c161] [c160] [c159] [c158] [c150] [c148] [c147] [c145] [c144] [c143] [c141] [c140] [c139] [c138] [c137] [c136] [c135] [c133] [c130] [c129] [c128] [c127] [c125] [c124] [c122] [c121] [c120] [c118] [c117] [c115] [c114] [c113] [c112] [c111] [c110] [c109] [c106] [c105] [c104] [c102] [c101] [c100] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c90] [c89] [c88] [c85] [c84] [c83] [c82] [c79] [c78] [c77] [c76] [c74] [c73] [c72] [c71] [c69] [c68] [c67] [c66] [c65] [c64] [c63] [c60] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1] [i37] [i36] [i35] [i30] [i29] [i28] [i27] [i25] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i3] [i2] [i1]
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