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Results for: Dang Nguyen

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs

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

2020 / Vol. 34, pp. 5256 - 5263 / Proceedings of the AAAI Conference on Artificial Intelligence

DeepCoDA: Personalized Interpretability for Compositional Health Data

T. Quinn, D. Nguyen, S. Rana, S. Gupta, S. Venkatesh

2020 / pp. 7877 - 7886 / Proceedings of the International Conference on Machine Learning (ICML)

Succinct contrast sets via false positive controlling with an application in clinical process redesign

D. Nguyen, W. Luo, B. Vo, W. Pedrycz

2020 / Vol. 161, pp. 113670 / Expert Systems with Applications

Learning distance-dependent motif interactions: an interpretable CNN model of genomic events

T. P. Quinn, D. Nguyen, P. Nguyen, S. Gupta, S. Venkatesh

2020 / bioRxiv

Factor Screening Using Bayesian Active Learning and Gaussian Process Meta-Modelling

C. Li, S. Rana, A. Gill, D. Nguyen, S. Gupta, S. Venkatesh

2020 / pp. in press / Systems Engineering Test and Evaluation Conference

Bayesian Optimization with Missing Inputs

P. Luong, D. Nguyen, S. Gupta, S. Rana, S. Venkatesh

2020 / Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)

Factor Screening High-Dimensional, Stochastic Combat Simulations

D. Nguyen, C. Li, S. Rana, A. Gill, S. Gupta, S. Venkatesh

2019

Efficient Bayesian Function Optimization of Evolving Material Manufacturing Processes

D. Rubín, D. Nguyen, P. Vellanki, C. Li, S. Rana, N. Thompson, S. Gupta, K. Pringle, S. Subianto, S. Venkatesh, O.

2019 / Vol. 4, pp. 20571 - 20578 / ACS omega

Detection of Compromised Models Using Bayesian Optimization

D. Kuttichira, S. Gupta, D. Nguyen, S. Rana, S. Venkatesh

2019 / pp. 485 - 496 / Australasian Joint Conference on Artificial Intelligence

Bayesian Optimization with Discrete Variables

P. Luong, S. Gupta, D. Nguyen, S. Rana, S. Venkatesh

2019 / pp. 473 - 484 / Australasian Joint Conference on Artificial Intelligence

Learning Graph Representation via Frequent Subgraphs

D. Nguyen, W. Luo, T. Nguyen, S. Venkatesh, D. Phung

2018 / pp. 306 - 314 / Proceedings of the 2018 SIAM International Conference on Data Mining (SDM)

Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets

D. Nguyen, T. Nguyen, W. Luo, S. Venkatesh

2018 / pp. 361 - 372 / Pacific-Asia Conference on Knowledge Discovery and Data Mining

Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding

D. Nguyen, W. Luo, S. Venkatesh, D. Phung

2018 / Vol. 42, pp. 94 / Journal of Medical Systems

LTARM: A novel temporal association rule mining method to understand toxicities in a routine cancer treatment

D. Nguyen, W. Luo, D. Phung, S. Venkatesh

2018 / Vol. 161, pp. 313 - 328 / Knowledge-Based Systems

Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint

D. Nguyen, W. Luo, T. Nguyen, S. Venkatesh, D. Phung

2018 / pp. 569 - 584 / The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)

Exceptional Contrast Set Mining: Moving beyond the deluge of the obvious

D. Nguyen, W. Luo, D. Phung, S. Venkatesh

2016 / pp. 455 - 468 / Proceedings of the 29th Australasian Joint Conference on Artificial Intelligence (AI 2016), Hobart, Australia, December,