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Scopus Author ID: 57225447616

Keywords

Artificial Intelligence, Bayesian Optimization, Trustworthy Machine Learning, Automated Machine Learning, Data-driven Software Engineering

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Employment (3)

RMIT University: Melbourne, AU

2025-01-01 to present | Senior Lecturer in Compute Science (School of Computing Technologies)
Employment
Source: Self-asserted source
Huong Ha

RMIT University: Melbourne, AU

2020-11-04 to 2024-12-31 | Lecturer in Computer Science (School of Computing Technologies)
Employment
Source: Self-asserted source
Huong Ha

Deakin University: Geelong, Victoria, AU

2018-10-01 to 2020-10-30 | Associate Research Fellow (Applied Artificial Intelligence Institute (A2I2))
Employment
Source: Self-asserted source
Huong Ha

Works (15)

High-dimensional bayesian optimization via covariance matrix adaptation strategy

Transaction of Machine Learning Research
2024-01 | Journal article
Source: Self-asserted source
Huong Ha

An Efficient Framework for Monitoring Subgroup Performance of Machine Learning Systems

The ML Safety Workshop at NeurIPS 2022
2022-12 | Conference poster
Source: Self-asserted source
Huong Ha

Bayesian preference learning for interactive multi-objective optimisation

Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)
2021-06-26 | Conference paper
Source: Self-asserted source
Huong Ha

High Dimensional Level Set Estimation with Bayesian Neural Network

The 35th AAAI Conference on Artificial Intelligence (AAAI 2021)
2021-02-09 | Conference paper
Source: Self-asserted source
Huong Ha

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces

Advances in Neural Information Processing Systems (NeurIPS'20)
2020-12-06 | Conference paper
Source: Self-asserted source
Huong Ha

Distributionally Robust Bayesian Quadrature Optimization

The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS'20)
2020-01-19 | Conference paper
Source: Self-asserted source
Huong Ha

Bayesian Optimization with Unknown Search Space

Advances in Neural Information Processing Systems 32
2019-12-06 | Book chapter
URI:

http://papers.nips.cc/paper/9350-bayesian-optimization-with-unknown-search-space.pdf
Source: Self-asserted source
Huong Ha

Performance-Influence Model for Highly Configurable Software with Fourier Learning and Lasso Regression

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)
2019-10-04 | Conference paper
DOI: 10.1109/ICSME.2019.00080
Source: Self-asserted source
Huong Ha

DeepPerf: Performance Prediction for Configurable Software with Deep Sparse Neural Network

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)
2019-05 | Conference paper
DOI: 10.1109/icse.2019.00113
ISBN: 9781728108698
Source: Self-asserted source
Huong Ha

An analysis of the SPARSEVA estimate for the finite sample data case

Automatica
2018-10-09 | Journal article
DOI: https://doi.org/10.1016/j.automatica.2018.06.046
Source: Self-asserted source
Huong Ha

Useful redundancy in parameter and time delay estimation for continuous-time models

Automatica
2018-09 | Journal article
DOI: 10.1016/j.automatica.2018.06.023
Part of ISSN: 0005-1098
Source: Self-asserted source
Huong Ha

Parameter and delay estimation of continuous-time models utilizing multiple filtering

2016 IEEE 55th Annual Conference on Decision and Control (CDC)
2016-12-25 | Conference paper
DOI: 10.1109/CDC.2016.7798430
Source: Self-asserted source
Huong Ha

Reweighted nuclear norm regularization: A SPARSEVA approach**This work was partially supported by the Swedish Research Council and the Linnaeus Center ACCESS at KTH.

IFAC-PapersOnLine
2015 | Conference paper
DOI: 10.1016/j.ifacol.2015.12.290
Part of ISSN: 2405-8963
Source: Self-asserted source
Huong Ha

Model order selection for continuous time instrumental variable methods using regularization

2015 54th IEEE Conference on Decision and Control (CDC)
2015-12 | Conference paper
DOI: 10.1109/cdc.2015.7402323
Part of ISBN: 9781479978861
Source: Self-asserted source
Huong Ha

Ensuring stability in continuous time system identification instrumental variable method for over-parameterized models

2014 IEEE 53rd Annual Conference on Decision and Control (CDC)
2014-12-15 | Conference paper
DOI: 10.1109/CDC.2014.7039786
Source: Self-asserted source
Huong Ha
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