Huong Ha

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Hongyu ZhangChongqing UniversityVerified email at newcastle.edu.au
James WelshUniversity of NewcastleVerified email at newcastle.edu.au
Svetha VenkateshAlfred Deakin Professor, Deakin UniversityVerified email at deakin.edu.au
Santu RanaAssociate Professor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Sunil GuptaProfessor, Head of AI Optimization and Materials Discovery, Deakin UniversityVerified email at deakin.edu.au
Vu NguyenAmazonVerified email at robots.ox.ac.uk
Thanh Nguyen-TangJohns Hopkins UniversityVerified email at cs.jhu.edu
Xingchen WanGoogleVerified email at google.com
Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Cong LuUniversity of British ColumbiaVerified email at cs.ubc.ca
Mazen AlamirCNRS, Université de GrenobleVerified email at gipsa-lab.grenoble-inp.fr
Bo WahlbergProfessor Automatic Control, KTH Royal Institute of TechnologyVerified email at kth.se
Cristian R. RojasProfessor, Division of Decision and Control Systems, KTH Royal Institute of TechnologyVerified email at kth.se
Jeffrey ChanSchool of Computing Technologies, RMIT UniversityVerified email at rmit.edu.au
Kendall TaylorRMIT UniversityVerified email at rmit.edu.au
Minyi LiSchool of Computing Technologies, RMIT UniversityVerified email at rmit.edu.au
Anton van den HengelDirector of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
Zongwen FanHuaqiao UniversityVerified email at hqu.edu.cn
Lam NgoRMIT University, AustraliaVerified email at student.rmit.edu.au

Huong Ha

Lecturer (Assistant Professor) of Computer Science, School of Computing Technologies, RMIT

Verified email at rmit.edu.au - Homepage

Statistical Modelling Artificial Intelligence Bayesian Optimization AutoML Trustworthy ML


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DeepPerf: performance prediction for configurable software with deep sparse neural network H Ha, H Zhang The 41st International Conference on Software Engineering (ICSE'19), 1095-1106, 2019	93	2019
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces X Wan, V Nguyen, H Ha, B Ru, C Lu, MA Osborne International Conference on Machine Learning (ICML'21), 2021	44	2021
Distributionally Robust Bayesian Quadrature Optimization TT Nguyen, S Gupta, H Ha, S Rana, S Venkatesh International Conference on Artificial Intelligence and Statistics (AISTATS'20), 2020	32	2020
Performance-Influence Model for Highly Configurable Software with Fourier Learning and Lasso Regression H Ha, H Zhang International Conference on Software Maintenance and Evolution (ICSME'19 …, 2019	29	2019
Bayesian Optimization with Unknown Search Space H Ha, S Rana, S Gupta, T Nguyen, H Tran-The, S Venkatesh Advances in Neural Information Processing Systems (NeurIPS'19), 2019	27	2019
Useful redundancy in parameter and time delay estimation for continuous-time models H Ha, JS Welsh, M Alamir Automatica 95, 455-462, 2018	24	2018
Bayesian preference learning for interactive multi-objective optimisation K Taylor, H Ha, M Li, J Chan, X Li Proceedings of the Genetic and Evolutionary Computation Conference (GECCO …, 2021	9	2021
High Dimensional Level Set Estimation with Bayesian Neural Network H Ha, S Gupta, S Rana, S Venkatesh The 35th AAAI Conference on Artificial Intelligence (AAAI'21), 2021	8	2021
Ensuring stability in continuous time system identification instrumental variable method for over-parameterized models H Ha, JS Welsh 2014 IEEE 53rd Annual Conference on Decision and Control (CDC), 2597-2602, 2014	8	2014
Reweighted nuclear norm regularization: A SPARSEVA approach H Ha, JS Welsh, N Blomberg, CR Rojas, B Wahlberg 2015 IFAC Symposium on System Identification (SYSID) 48 (28), 1172-1177, 2015	7	2015
Parameter and delay estimation of continuous-time models utilizing multiple filtering H Ha, JS Welsh 2016 IEEE 55th Annual Conference on Decision and Control (CDC), 1205-1210, 2016	6	2016
Model Order Selection for Continuous Time Instrumental Variable Methods Using Regularization H Ha, JS Welsh 2015 IEEE 54th Annual Conference on Decision and Control (CDC), 771-776, 2015	5	2015
Provably Efficient Bayesian Optimization with Unbiased Gaussian Process Hyperparameter Estimation H Ha, V Nguyen, H Zhang, A Hengel arXiv preprint arXiv:2306.06844, 2023	3	2023
An analysis of the SPARSEVA estimate for the finite sample data case H Ha, JS Welsh, CR Rojas, B Wahlberg Automatica 96, 141-149, 2018	3	2018
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces H Tran-The, S Gupta, S Rana, H Ha, S Venkatesh Advances in Neural Information Processing Systems (NeurIPS'20), 2020	1*	2020
High-dimensional bayesian optimization via covariance matrix adaptation strategy L Ngo, H Ha, J Chan, V Nguyen, H Zhang Transaction of Machine Learning Research, 2024		2024
Uncertainty-Aware Performance Prediction for Highly Configurable Software Systems via Bayesian Neural Networks H Ha, Z Fan, H Zhang arXiv:2212.13359, 2022, 2022		2022
An Efficient Framework for Monitoring Subgroup Performance of Machine Learning Systems H Ha ML Safety Workshop at NeurIPS'22, 2022		2022
ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms H Ha, S Gupta, S Rana, S Venkatesh RobustML workshop at ICLR'21, 2021		2021

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