Haitao Liu (刘海涛)

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Yew-Soon OngPresident Chair Professor of Computer Science, A*Star AI Chief Scientist, FIEEEVerified email at ntu.edu.sg
Jianfei CaiProfessor of Data Science & AI, Monash UniversityVerified email at monash.edu
徐胜利 (Shengli Xu)大连理工大学Verified email at dlut.edu.cn
Xiaobo ShenNanjing University of Science and TechnologyVerified email at njust.edu.cn
Xiaomo JiangDalian University of TechnologyVerified email at dlut.edu.cn
Yi WangNational Supercomputing Centre SingaporeVerified email at nscc.sg
Zhendong Guo(郭振东)Xi'an Jiaotong University(西安交通大学)Verified email at xjtu.edu.cn
luo jianpingshenzhen universityVerified email at szu.edu.cn
Zhenkun Wang（王振坤）Southern University of Science and Technology (SUSTech)Verified email at sustech.edu.cn
Qingfu ZhangChair Professor, FIEEE, City University of Hong KongVerified email at cityu.edu.hk
Shunyu YaoCity University of Hong KongVerified email at my.cityu.edu.hk
Ziwei YuNational University of Singapore SoC Ph.D StudentVerified email at u.nus.edu
Jaime Rubio HervasResearch Fellow, Nanyang Technological UniversityVerified email at ntu.edu.sg
Bingshui DaNanyang Technological UniversityVerified email at e.ntu.edu.sg
Liang FengChongqing UniversityVerified email at cqu.edu.cn
Abhishek GuptaRamanujan Faculty Fellow, IIT Goa; (formerly Scientist at A*STAR and NTU Singapore)Verified email at iitgoa.ac.in
Xinghua QuBytedance SeedVerified email at bytedance.com
Jianmin ZhengSchool of Computer Science and Engineering, Nanyang Technological UniversityVerified email at ntu.edu.sg
Jinguang YangDalian University of TechnologyVerified email at dlut.edu.cn
Adil MalikHarbin Engineering University, National University of Science and TechnologyVerified email at hrbeu.edu.cn

Haitao Liu (刘海涛)

Associate Professor, Dalian University of Technology

Verified email at dlut.edu.cn - Homepage

Gaussian Process Deep Learning Active learning Multi-task learning Design & Optimization


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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	982	2020
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	470	2018
Remarks on multi-output Gaussian process regression H Liu, J Cai, YS Ong Knowledge-Based Systems, 1-20, 2018	312	2018
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	148	2014
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	131	2017
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	119	2018
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	79	2017
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	77	2016
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	63	2016
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	56	2015
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	52	2021
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	45	2017
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	37	2020
Sequential sampling designs based on space reduction H Liu, S Xu, X Wang Engineering Optimization 47 (7), 867-884, 2015	35	2015
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	31	2019
Fast Transfer Gaussian Process Regression with Large-Scale Sources B Da, YS Ong, A Gupta, L Feng, H Liu Knowledge-Based Systems, 2018	31	2018
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	31	2018
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	19	2015
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	18	2018
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	18	2016

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