Haitao Liu

According to our database, Haitao Liu authored at least 20 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Learning Multitask Gaussian Process Over Heterogeneous Input Domains.

Haitao Liu, Kai Wu, Yew-Soon Ong, Chao Bian, Xiaomo Jiang, Xiaofang Wang

IEEE Trans. Syst. Man Cybern. Syst., October, 2023

Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization.

Zhenkun Wang, Qingfu Zhang, Yew-Soon Ong, Shunyu Yao, Haitao Liu, Jianping Luo

IEEE Trans. Cybern., 2023

Generative Multiform Bayesian Optimization.

Zhendong Guo, Haitao Liu, Yew-Soon Ong, Xinghua Qu, Yuzhe Zhang, Jianmin Zheng

IEEE Trans. Cybern., 2023

2022

Scalable Gaussian Process Classification With Additive Noise for Non-Gaussian Likelihoods.

Haitao Liu, Yew-Soon Ong, Ziwei Yu, Jianfei Cai, Xiaobo Shen

IEEE Trans. Cybern., 2022

Deep Latent-Variable Kernel Learning.

Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

IEEE Trans. Cybern., 2022

Co-Learning Bayesian Optimization.

Zhendong Guo, Yew-Soon Ong, Tiantian He, Haitao Liu

IEEE Trans. Cybern., 2022

Scalable multi-task Gaussian processes with neural embedding of coregionalization.

Haitao Liu, Jiaqi Ding, Xinyu Xie, Xiaomo Jiang, Yusong Zhao, Xiaofang Wang

Knowl. Based Syst., 2022

Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains.

Haitao Liu, Kai Wu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

CoRR, 2022

2021

Large-Scale Heteroscedastic Regression via Gaussian Process.

Haitao Liu, Yew-Soon Ong, Jianfei Cai

IEEE Trans. Neural Networks Learn. Syst., 2021

Modulating scalable Gaussian processes for expressive statistical learning.

Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

Pattern Recognit., 2021

Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems.

Haitao Liu, Changjun Liu, Xiaomo Jiang, Xudong Chen, Shuhua Yang, Xiaofang Wang

CoRR, 2021

2020

When Gaussian Process Meets Big Data: A Review of Scalable GPs.

Haitao Liu, Yew-Soon Ong, Xiaobo Shen, Jianfei Cai

IEEE Trans. Neural Networks Learn. Syst., 2020

2019

Understanding and comparing scalable Gaussian process regression for big data.

Haitao Liu, Jianfei Cai, Yew-Soon Ong, Yi Wang

Knowl. Based Syst., 2019

Fast transfer Gaussian process regression with large-scale sources.

Bingshui Da, Yew-Soon Ong, Abhishek Gupta, Liang Feng, Haitao Liu

Knowl. Based Syst., 2019

Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods.

Haitao Liu, Yew-Soon Ong, Ziwei Yu, Jianfei Cai, Xiaobo Shen

CoRR, 2019

2018

Remarks on multi-output Gaussian process regression.

Haitao Liu, Jianfei Cai, Yew-Soon Ong

Knowl. Based Syst., 2018

Cope with diverse data structures in multi-fidelity modeling: A Gaussian process method.

Haitao Liu, Yew-Soon Ong, Jianfei Cai, Yi Wang

Eng. Appl. Artif. Intell., 2018

Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression.

Haitao Liu, Jianfei Cai, Yi Wang, Yew-Soon Ong

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

An adaptive sampling approach for Kriging metamodeling by maximizing expected prediction error.

Haitao Liu, Jianfei Cai, Yew-Soon Ong

Comput. Chem. Eng., 2017

2015

Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces.

Haitao Liu, Shengli Xu, Ying Ma, Xiaofang Wang

J. Glob. Optim., 2015