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2020 – today
- 2024
[j27]Hung-Kai Pi, Meihui Guo, Ray-Bing Chen, Shih-Feng Huang:
ECOPICA: empirical copula-based independent component analysis. Stat. Comput. 34(1): 52 (2024)- 2023
- [j26]Fan Zhang
, Ray-Bing Chen, Ying Hung, Xinwei Deng:
Indicator-based Bayesian variable selection for Gaussian process models in computer experiments. Comput. Stat. Data Anal. 185: 107757 (2023) - 2022
- [j25]Wei-Ting Lai, Ray-Bing Chen, Ying Chen, Thorsten Koch:
Variational Bayesian inference for network autoregression models. Comput. Stat. Data Anal. 169: 107406 (2022) - 2020
- [j24]Liang-Ching Lin, Ray-Bing Chen, Mong-Na Lo Huang, Meihui Guo:
Huber-type principal expectile component analysis. Comput. Stat. Data Anal. 151: 106992 (2020) - [j23]Ray-Bing Chen, Yuan Wang, C. F. Jeff Wu:
Finding optimal points for expensive functions using adaptive RBF-based surrogate model via uncertainty quantification. J. Glob. Optim. 77(4): 919-948 (2020) - [i1]Ray-Bing Chen, Yuan Wang, Chien-Fu Jeff Wu:
Finding Optimal Points for Expensive Functions Using Adaptive RBF-Based Surrogate Model Via Uncertainty Quantification. CoRR abs/2001.06858 (2020)
2010 – 2019
- 2019
- [j22]Hsiang-Ling Hsu, Yuan-chin Ivan Chang, Ray-Bing Chen:
Greedy active learning algorithm for logistic regression models. Comput. Stat. Data Anal. 129: 119-134 (2019) - [j21]Ying Chen, Linlin Niu, Ray-Bing Chen, Qiang He:
Sparse-Group Independent Component Analysis with application to yield curves prediction. Comput. Stat. Data Anal. 133: 76-89 (2019) - [j20]Yuan-chin Ivan Chang, Ray-Bing Chen:
Active learning with simultaneous subject and variable selections. Neurocomputing 329: 495-505 (2019) - 2018
- [j19]Ping-Yang Chen, Ray-Bing Chen, C. Devon Lin:
Optimizing two-level orthogonal arrays for simultaneously estimating main effects and pre-specified two-factor interactions. Comput. Stat. Data Anal. 118: 84-97 (2018) - 2017
- [j18]Ray-Bing Chen, Weichung Wang, C. F. Jeff Wu:
Sequential Designs Based on Bayesian Uncertainty Quantification in Sparse Representation Surrogate Modeling. Technometrics 59(2): 139-152 (2017) - [c5]Ping-Yang Chen, Chi-Chun Hsia, Yen-Hao Su, Ray-Bing Chen, Sheng-Mao Chang:
Feedback Control for Binary Response. TAAI 2017: 21-24 - 2016
- [j17]Kuo-Jung Lee, Ray-Bing Chen, Ying Nian Wu:
Bayesian variable selection for finite mixture model of linear regressions. Comput. Stat. Data Anal. 95: 1-16 (2016) - [j16]Sheng-Mao Chang, Ray-Bing Chen, Yunchan Chi:
Bayesian Variable Selections for Probit Models with Componentwise Gibbs Samplers. Commun. Stat. Simul. Comput. 45(8): 2752-2766 (2016) - [j15]Frederick Kin Hing Phoa, Ray-Bing Chen, Weichung Wang, Weng Kee Wong:
Optimizing Two-Level Supersaturated Designs Using Swarm Intelligence Techniques. Technometrics 58(1): 43-49 (2016) - [c4]Mu Yang, Ray-Bing Chen, I-Hsin Chung, Weichung Wang:
Particle Swarm Stepwise Algorithm (PaSS) on Multicore Hybrid CPU-GPU Clusters. CIT 2016: 265-272 - 2015
- [j14]Kuo-Jung Lee, Ray-Bing Chen:
BSGS: Bayesian Sparse Group Selection. R J. 7(2): 122 (2015) - [j13]Ray-Bing Chen, Meihui Guo, Wolfgang K. Härdle, Shih-Feng Huang:
COPICA - independent component analysis via copula techniques. Stat. Comput. 25(2): 273-288 (2015) - [j12]Ray-Bing Chen, Shin-Perng Chang, Weichung Wang, Heng-Chih Tung, Weng Kee Wong:
Minimax optimal designs via particle swarm optimization methods. Stat. Comput. 25(5): 975-988 (2015) - [c3]Ponnuswamy Sadayappan, Ray-Bing Chen:
iWAPT Invited Talks. IPDPS Workshops 2015: 1202-1203 - 2014
- [j11]Ray-Bing Chen, Yen-Wen Hsu, Ying Hung, Weichung Wang:
Discrete particle swarm optimization for constructing uniform design on irregular regions. Comput. Stat. Data Anal. 72: 282-297 (2014) - [j10]Ray-Bing Chen, Ying Chen, Wolfgang K. Härdle:
TVICA - Time varying independent component analysis and its application to financial data. Comput. Stat. Data Anal. 74: 95-109 (2014) - [j9]Ray-Bing Chen, Yaohung M. Tsai, Weichung Wang:
Adaptive block size for dense QR factorization in hybrid CPU-GPU systems via statistical modeling. Parallel Comput. 40(5-6): 70-85 (2014) - [j8]Jiaheng Qiu, Ray-Bing Chen, Weichung Wang, Weng Kee Wong:
Using animal instincts to design efficient biomedical studies via particle swarm optimization. Swarm Evol. Comput. 18: 1-10 (2014) - [c2]Wan-Ping Chen, Ying Nian Wu, Ray-Bing Chen:
Bayesian Variable Selection for Multi-response Linear Regression. TAAI 2014: 74-88 - 2013
- [j7]Ray-Bing Chen, Ying-Chao Hung, Weichung Wang, Sung-Wei Yen:
Contour estimation via two fidelity computer simulators under limited resources. Comput. Stat. 28(4): 1813-1834 (2013) - [j6]Ray-Bing Chen, Jian-Zhong Weng, Chi-Hsiang Chu:
Screening Procedure for Supersaturated Designs Using a Bayesian Variable Selection Method. Qual. Reliab. Eng. Int. 29(1): 89-101 (2013) - [j5]Ray-Bing Chen, Dai-Ni Hsieh, Ying Hung, Weichung Wang:
Optimizing Latin hypercube designs by particle swarm. Stat. Comput. 23(5): 663-676 (2013) - 2012
- [c1]Yaohung M. Tsai, Weichung Wang, Ray-Bing Chen:
Tuning Block Size for QR Factorization on CPU-GPU Hybrid Systems. MCSoC 2012: 205-211 - 2011
- [j4]Weichung Wang, Ray-Bing Chen, Chia-Lung Hsu:
Using adaptive multi-accurate function evaluations in a surrogate-assisted method for computer experiments. J. Comput. Appl. Math. 235(10): 3151-3162 (2011) - [j3]Ray-Bing Chen, Chi-Hsiang Chu, Te-You Lai, Ying Nian Wu:
Stochastic matching pursuit for Bayesian variable selection. Stat. Comput. 21(2): 247-259 (2011) - 2010
- [j2]Mong-Na Lo Huang, Chuan-Pin Lee, Ray-Bing Chen, Thomas Klein:
Exact D-optimal designs for a second-order response surface model on a circle with qualitative factors. Comput. Stat. Data Anal. 54(2): 516-530 (2010)
2000 – 2009
- 2007
- [j1]Ray-Bing Chen, Ying Nian Wu:
A null space method for over-complete blind source separation. Comput. Stat. Data Anal. 51(12): 5519-5536 (2007)
Coauthor Index
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