Dinh Phung
Cited by
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Activity recognition and abnormality detection with the switching hidden semi-markov model
TV Duong, HH Bui, DQ Phung, S Venkatesh
2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005
Labeled random finite sets and the Bayes multi-target tracking filter
BN Vo, BT Vo, D Phung
IEEE Transaction on Signal Processing, 2014
Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model
N Nguyen, DQ Phung, S Venkatesh, H Bui
Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer …, 2005
Deepcare: A deep dynamic memory model for predictive medicine
T Pham, T Tran, D Phung, S Venkatesh
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 30-41, 2016
Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view
W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ...
Journal of medical Internet research 18 (12), e323, 2016
Predicting healthcare trajectories from medical records: A deep learning approach
T Pham, T Tran, D Phung, S Venkatesh
Journal of biomedical informatics 69, 218-229, 2017
A novel embedding model for knowledge base completion based on convolutional neural network
DQ Nguyen, TD Nguyen, DQ Nguyen, D Phung
arXiv preprint arXiv:1712.02121, 2017
Dual discriminator generative adversarial nets
T Nguyen, T Le, H Vu, D Phung
Advances in Neural Information Processing Systems, 2670-2680, 2017
Affective and Content Analysis of Online Depression Communities
T Nguyen, D Phung, B Dao, S Venkatesh, M Berk
IEEE Transaction on Affective Computing, 1-1, 2014
Efficient duration and hierarchical modeling for human activity recognition
T Duong, D Phung, H Bui, S Venkatesh
Artificial Intelligence 173 (7-8), 830-856, 2009
MGAN: Training generative adversarial nets with multiple generators
Q Hoang, TD Nguyen, T Le, D Phung
International Conference on Learning Representation (ICLR), 2018
Hierarchical hidden Markov models with general state hierarchy
HH Bui, DQ Phung, S Venkatesh
Proceedings of the national conference on artificial intelligence, 324-329, 2004
Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
T Tran, TD Nguyen, D Phung, S Venkatesh
Journal of biomedical informatics 54, 96-105, 2015
Column networks for collective classification
T Pham, T Tran, D Phung, S Venkatesh
arXiv preprint arXiv:1609.04508, 2016
Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments
T Tran, W Luo, D Phung, R Harvey, M Berk, RL Kennedy, S Venkatesh
BMC psychiatry 14 (1), 76, 2014
Nonnegative shared subspace learning and its application to social media retrieval
SK Gupta, D Phung, B Adams, T Tran, S Venkatesh
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso
I Kamkar, SK Gupta, D Phung, S Venkatesh
Journal of biomedical informatics 53, 277-290, 2015
Ordinal Boltzmann machines for collaborative filtering
T Tran, DQ Phung, S Venkatesh
Arxiv preprint arXiv:1205.2611, 2009
Sensing and using social context
B Adams, D Phung, S Venkatesh
ACM Transactions on Multimedia Computing, Communications, and Applications …, 2008
Extraction of social context and application to personal multimedia exploration
B Adams, D Phung, S Venkatesh
Proceedings of the 14th ACM international conference on Multimedia, 987-996, 2006
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