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Bayesian Multi-Hyperplane Machine for Pattern Recognition

K. Nguyen, T. Le, T. Dinh, D. Phung

2018 / pp. 609 - 614 / 2018 24th International Conference on Pattern Recognition (ICPR)

Robust Bayesian kernel machine via stein variational gradient descent for big data

K. Nguyen, T. Le, T. Nguyen, D. Phung, G. I. Webb

2018 / pp. 2003 - 2011 / Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

MGAN: Training generative adversarial nets with multiple generators

Q. Hoang, T. Nguyen, T. Le, D. Phung

2018 / In International Conference on Learning Representations

Exploiting Strategy-Space Diversity for Batch Bayesian Optimization

S. Gupta, A. Shilton, S. Rana, S. Venkatesh

2018 / pp. 538 - 547 / The 21st International Conference on Artificial Intelligence and Statistics

New Bayesian-Optimization-Based Design of High-Strength 7xxx-Series Alloys from Recycled Aluminum

A. Vahid, S. Rana, S. Gupta, P. Vellanki, S. Venkatesh, T. Dorin

2018 / Vol. 70, pp. 2704 - 2709 / The Journal of The Minerals, Metals and Materials Society (JOM)

A Privacy Preserving Bayesian Optimization with High Efficiency

N. Dai, S. Gupta, S. Rana, S. Venkatesh

2018 / pp. 543 - 555 / Pacific-Asia Conference on Knowledge Discovery and Data Mining

Discovering topic structures of a temporally evolving document corpus

A. Beykikhoshk, O. Arandjelovic, D. Phung, S. Venkatesh

2018 / Vol. 55, pp. 599 - 632 / Knowledge and Information Systems

Differentially Private Prescriptive Analytics

H. Harikumar, S. Rana, S. Gupta, T. Nguyen, R. Kaimal, S. Venkatesh

2018 / pp. 995 - 1000 / 2018 IEEE International Conference on Data Mining (ICDM)

A deep learning model for estimating story points

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

2018 / IEEE Transactions on Software Engineering

Predicting delivery capability in iterative software development

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

2018 / Vol. 44, pp. 551 - 573 / IEEE Transactions on Software Engineering

Energy-Based Anomaly Detection for Mixed Data

K. Do, T. Tran, S. Venkatesh

2018 / Vol. 57, pp. 413 - 435 / Knowledge and Information Systems

Automatic feature learning for predicting vulnerable software components

H. Dam, T. Tran, T. Pham, S. Ng, J. Grundy, A. Ghose

2018 / IEEE Transactions on Software Engineering

Neural reasoning for chemical-chemical interaction

T. Pham, T. Tran, S. Venkatesh

2018 / NeurIPS 2018 Workshop on Machine Learning for Molecules and Materials

Committee machine that votes for similarity between materials

D. Nguyen, T. Pham, V. Nguyen, T. Ho, T. Tran, K. Takahashi, H. Dam

2018 / Vol. 5 / IUCrJ

On catastrophic forgetting and mode collapse in Generative Adversarial Networks

H. Thanh-Tung, T. Tran, S. Venkatesh

2018 / ICML Workshop on Theoretical Foundations and Applications of Deep Generative Models

Explainable software analytics

H. Dam, T. Tran, A. Ghose

2018 / pp. 53 - 56 / Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results

Predicting components for issue reports using deep learning with information retrieval

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

2018 / pp. 244 - 245 / Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings