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Results for: 2017

Approximation vector machines for large-scale online learning

T. Le, T. Nguyen, V. Nguyen, D. Phung

2017 / Vol. 18, pp. 3962 - 4016 / The Journal of Machine Learning Research

High Dimensional Bayesian Optimization Using Dropout

C. Li, S. Gupta, S. Rana, V. Nguyen, S. Venkatesh, A. Shilton

2017 / pp. 2096 - 2102 / International Joint Conference on Artificial Intelligence

A Generic Neural Architecture for Multiple Inputs and Outputs

T. Pham, T. Tran, S. Venkatesh

2017 / NIPS Workshop on Women in Machine Learning (WiML 2017)

Finding Algebraic Structure of Care in Time: A Deep Learning Approach

P. Nguyen, T. Tran, S. Venkatesh

2017 / NIPS Workshop on Machine Learning for Health (ML4H)

Preference Relation-based Markov Random Fields for Recommender Systems

S. Liu, G. Li, T. Tran, J. Yuan

2017 / Vol. 246, pp. 523 - 546 / Machine Learning

Learning Recurrent Matrix Representation

K. Do, T. Tran, S. Venkatesh

2017 / Third Representation Learning for Graphs Workshop (ReLiG 2017)

Graph Classification via Deep Learning with Virtual Nodes

T. Pham, T. Tran, H. Dam, S. Venkatesh

2017 / Third Representation Learning for Graphs Workshop (ReLiG 2017)

Predicting the delay of issues with due dates in software projects

M. Choetkiertikul, H. Dam, T. Tran, A. Ghose

2017 / Vol. 22, pp. 1223 - 1263 / Empirical Software Engineering

Deepr: A Convolutional Net for Medical Records

P. Nguyen, T. Tran, N. Wickramasinghe, S. Venkatesh

2017 / Vol. 21, pp. 22 - 30 / IEEE journal of biomedical and health informatics

Deep learning to attend to risk in ICU

P. Nguyen, T. Tran, S. Venkatesh

2017 / pp. 25 - 29 / KDH 2017: Proceedings of the 2nd International Workshop on Knowledge Discovery in Healthcare Data 2017

Energy-Based Localized Anomaly Detection in Video Surveillance

H. Vu, T. Nguyen, A. Travers, S. Venkatesh, D. Phung

2017 / pp. 641 - 653 / Pacific-Asia Conference on Knowledge Discovery and Data Mining

Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions

B. Saha, S. Gupta, D. Phung, S. Venkatesh

2017 / Vol. 53, pp. 1 - 28 / Knowledge and Information Systems

Machine Learning in Healthcare: An Investigation into Model Stability

S. Gopakumar

2017 / Doctor of Philosophy (Information Technology), School of Information Technology

Dual discriminator generative adversarial nets

T. Nguyen, T. Le, H. Vu, D. Phung

2017 / pp. 2670 - 2680 / Advances in Neural Information Processing Systems

Supervised Restricted Boltzmann Machines.

T. Nguyen, D. Q. Phung, V. Huynh, T. Le

2017 / UAI

Multilevel clustering via wasserstein means

N. Ho, X. Nguyen, M. Yurochkin, H. Bui, V. Huynh, D. Phung

2017 / pp. 1501 - 1509 / Proceedings of the 34th International Conference on Machine Learning-Volume 70

Large-scale Online Kernel Learning with Random Feature Reparameterization.

T. Nguyen, T. Le, H. Bui, D. Q. Phung

2017 / pp. 2543 - 2549 / IJCAI

Streaming clustering with Bayesian nonparametric models

V. Huynh, D. Phung

2017 / Vol. 258, pp. 52 - 62 / Neurocomputing