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Benben Jiang
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2020 – today
- 2024
- [j15]Xiaobin Song, Zeyuan Liu, Benben Jiang:
Adaptive boosting with fairness-aware reweighting technique for fair classification. Expert Syst. Appl. 250: 123916 (2024) - [j14]Yuhan Hao, Qiugang Lu, Xizhe Wang, Benben Jiang:
Adaptive Model-Based Reinforcement Learning for Fast-Charging Optimization of Lithium-Ion Batteries. IEEE Trans. Ind. Informatics 20(1): 127-137 (2024) - [i3]Xiaobin Song, Zeyuan Liu, Benben Jiang:
Adaptive Boosting with Fairness-aware Reweighting Technique for Fair Classification. CoRR abs/2401.03097 (2024) - 2023
- [j13]Zeyuan Liu, Xin Zhang, Benben Jiang:
Active learning with fairness-aware clustering for fair classification considering multiple sensitive attributes. Inf. Sci. 647: 119521 (2023) - [j12]Hongbo Zhao, Haitao Dean Deng, Alexander E. Cohen, Jongwoo Lim, Yiyang Li, Dimitrios Fraggedakis, Benben Jiang, Brian D. Storey, William C. Chueh, Richard D. Braatz, Martin Z. Bazant:
Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel. Nat. 621(7978): 289-294 (2023) - [i2]Benben Jiang, Yixing Wang, Zhenghua Ma, Qiugang Lu:
Fast Charging of Lithium-Ion Batteries Using Deep Bayesian Optimization with Recurrent Neural Network. CoRR abs/2304.04195 (2023) - [i1]Xiaobin Song, Benben Jiang:
Parallel Bayesian Optimization Using Satisficing Thompson Sampling for Time-Sensitive Black-Box Optimization. CoRR abs/2310.12526 (2023) - 2022
- [j11]Benben Jiang, Qiugang Lu:
Fault Detection in Industrial Systems Using Maximized Divergence Analysis Approach. IEEE Access 10: 60674-60681 (2022) - [j10]Benben Jiang, Xizhe Wang:
Constrained Bayesian Optimization for Minimum-Time Charging of Lithium-Ion Batteries. IEEE Control. Syst. Lett. 6: 1682-1687 (2022) - [j9]Benben Jiang, Bofan Zhu:
Dynamic Bhattacharyya Bound-Based Approach for Fault Classification in Industrial Processes. IEEE Trans. Ind. Informatics 18(1): 397-404 (2022) - [c3]Marc D. Berliner, Benben Jiang, Daniel A. Cogswell, Martin Z. Bazant, Richard D. Braatz:
Fast Charging of Lithium-ion Batteries by Mathematical Reformulation as Mixed Continuous-Discrete Simulation. ACC 2022: 5265-5270 - 2021
- [j8]Qiugang Lu, Benben Jiang, Eranda Harinath:
Fault Diagnosis in Industrial Processes by Maximizing Pairwise Kullback-Leibler Divergence. IEEE Trans. Control. Syst. Technol. 29(2): 780-785 (2021)
2010 – 2019
- 2019
- [j7]Benben Jiang, Zhifeng Guo, Qunxiong Zhu, Gao Huang:
Dynamic Minimax Probability Machine-Based Approach for Fault Diagnosis Using Pairwise Discriminate Analysis. IEEE Trans. Control. Syst. Technol. 27(2): 806-813 (2019) - [j6]Benben Jiang, Yi Luo, Qiugang Lu:
Maximized Mutual Information Analysis Based on Stochastic Representation for Process Monitoring. IEEE Trans. Ind. Informatics 15(3): 1579-1587 (2019) - [j5]Benben Jiang, Xiaoxiang Zhu:
Latent variable modeling approach for fault detection and identification of process correlations. Trans. Inst. Meas. Control 41(6): 1740-1749 (2019) - 2018
- [j4]Qiugang Lu, Benben Jiang, R. Bhushan Gopaluni, Philip D. Loewen, Richard D. Braatz:
Locality preserving discriminative canonical variate analysis for fault diagnosis. Comput. Chem. Eng. 117: 309-319 (2018) - 2017
- [c2]Benben Jiang, Zhifeng Guo, Qunxiong Zhu, Gao Huang:
Pairwise discriminate analysis based minimax probability machine (PDA-MPM) approach for fault diagnosis. CCTA 2017: 1486-1491 - 2015
- [j3]Benben Jiang, Fan Yang, Wei Wang, Dexian Huang:
Simultaneous identification of bi-directional paths in closed-loop systems with coloured noise. Autom. 58: 139-142 (2015) - [j2]Benben Jiang, Xiaoxiang Zhu, Dexian Huang, Joel A. Paulson, Richard D. Braatz:
A combined canonical variate analysis and Fisher discriminant analysis (CVA-FDA) approach for fault diagnosis. Comput. Chem. Eng. 77: 1-9 (2015) - [j1]Benben Jiang, Fan Yang, Wei Wang, Dexian Huang:
Simultaneous Identification of Bidirectional Path Models Based on Process Data. IEEE Trans Autom. Sci. Eng. 12(2): 666-679 (2015) - 2013
- [c1]Benben Jiang, Fan Yang, Dexian Huang, Wei Wang:
Extended-AUDI method for simultaneous determination of causality and models from process data. ACC 2013: 2491-2496
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