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Haitao Liu (刘海涛)
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When Gaussian process meets big data: A review of scalable GPs
H Liu, YS Ong, X Shen, J Cai
IEEE transactions on neural networks and learning systems 31 (11), 4405-4423, 2020
8962020
A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design
H Liu, YS Ong, J Cai
Structural and Multidisciplinary Optimization 57, 393-416, 2018
4312018
Remarks on multi-output Gaussian process regression
H Liu, J Cai, YS Ong
Knowledge-Based Systems, 1-20, 2018
2842018
A robust error-pursuing sequential sampling approach for global metamodeling based on voronoi diagram and cross validation
S Xu, H Liu, X Wang, X Jiang
Journal of Mechanical Design 136 (7), 071009, 2014
1382014
An adaptive sampling approach for Kriging metamodeling by maximizing expected prediction error
H Liu, J Cai, YS Ong
Computers & Chemical Engineering 106, 171-182, 2017
1272017
Generalized robust Bayesian committee machine for large-scale Gaussian process regression
H Liu, J Cai, Y Wang, YS Ong
International Conference on Machine Learning, 3131-3140, 2018
1122018
Cope with diverse data structures in multi-fidelity modeling: A Gaussian process method
H Liu, YS Ong, J Cai, Y Wang
Engineering Applications of Artificial Intelligence, 211-225, 2017
752017
An adaptive Bayesian sequential sampling approach for global metamodeling
H Liu, S Xu, Y Ma, X Chen, X Wang
Journal of Mechanical Design 138 (1), 011404, 2016
752016
Optimal weighted pointwise ensemble of radial basis functions with different basis functions
H Liu, S Xu, X Wang, J Meng, S Yang
AIAA Journal 54 (10), 3117-3133, 2016
612016
A global optimization algorithm for simulation-based problems via the extended DIRECT scheme
H Liu, S Xu, X Wang, J Wu, Y Song
Engineering Optimization 47 (11), 1441-1458, 2015
562015
Choose appropriate subproblems for collaborative modeling in expensive multiobjective optimization
Z Wang, Q Zhang, YS Ong, S Yao, H Liu, J Luo
IEEE Transactions on Cybernetics 53 (1), 483-496, 2021
452021
Constrained global optimization via a DIRECT-type constraint-handling technique and an adaptive metamodeling strategy
H Liu, S Xu, X Chen, X Wang, Q Ma
Structural and Multidisciplinary Optimization 55, 155-177, 2017
422017
Sequential sampling designs based on space reduction
H Liu, S Xu, X Wang
Engineering Optimization 47 (7), 867-884, 2015
352015
Large-scale heteroscedastic regression via Gaussian process
H Liu, YS Ong, J Cai
IEEE transactions on neural networks and learning systems 32 (2), 708-721, 2020
302020
An adaptive RBF-HDMR modeling approach under limited computational budget
H Liu, JR Hervas, YS Ong, J Cai, Y Wang
Structural and Multidisciplinary Optimization 57, 1233-1250, 2018
292018
Understanding and comparing scalable Gaussian process regression for big data
H Liu, J Cai, YS Ong, Y Wang
Knowledge-Based Systems 164, 324-335, 2019
282019
Fast Transfer Gaussian Process Regression with Large-Scale Sources
B Da, YS Ong, A Gupta, L Feng, H Liu
Knowledge-Based Systems, 2018
282018
Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces
H Liu, S Xu, Y Ma, X Wang
Journal of Global optimization 63 (2), 229-251, 2015
192015
Sampling strategies and metamodeling techniques for engineering design: comparison and application
H Liu, S Xu, X Wang
Turbo Expo: Power for Land, Sea, and Air 49712, V02CT45A019, 2016
172016
A multi-response adaptive sampling approach for global metamodeling
H Liu, S Xu, X Wang, S Yang, J Meng
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of …, 2018
162018
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Articles 1–20