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陈洪
发布时间:2015-05-18

  

陈洪, 教授,博士生导师,湖北省优秀博士论文获得者。研究方向为机器学习、统计学习理论、逼近论。

主持国家自然科学基金面上项目、国家自然科学基金青年基金项目、校优秀人才培育项目、校创新团队培育项目等多项科研课。发表SCI论文30余篇,包括Applied and Computational Harmonic Analysis,IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics, Neural Computation, Neural Networks, Journal of Approximation Theory等知名学术期刊,在机器学习顶级会议Annual Conference on Neural Information Processing Systems (NIPS)发表论文3篇。2016.3-2017.8受美方资助作为高级研究助手在University of Texas at Arlington从事合作研究,多次受邀请和资助赴澳门大学、香港城市大学等进行合作研究。

招生专业: 农业信息工程 (博士)、应用数学(硕士)、应用统计(硕士)

招生意向: 有较好的数学、统计学基础和编程能力,有志于从事统计机器学习领域前沿课题的研究。

代表期刊论文:

[1]Yulong Wang, Yuan Yan Tang, Luoqing Li, Hong Chen, Jianjia Pan. Atomic representation-based classification: theory, algorithm and applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2017.2780094

[2]Hong Chen, Yulong Wang. Kernel-based sparse regression with the correntropy-induced loss, Applied and Computational Harmonic Analysis, 44(1): 144-164, 2018.

[3]Tieliang Gong, Zongben Xu, Hong Chen. Generalization analysis of Fredholm kernel regularized classifiers , Neural Computation, 29(7): 1879-1901, 2017.

[4]Yicong Zhou, Hong Chen, Rushi Lan, Zhibin Pan.Generalization performance of regularized ranking with multiscale kernels. IEEE Trans. Neural Netw. Learning Syst., 27: 993-1002, 2016.

[5] Hong Chen, Jiangtao Peng, Yicong Zhou, Zhibin Pan. Extreme learning machine for ranking: generalization analysis and applications, Neural Networks, 53: 119--126, 2014.

[6] Hong Chen, Yi Tang, Luoqing Li, Yuan Yuan, Xuelong Li, Yuan-Yan Tang. Error analysis of stochastic gradient descent ranking, IEEE Transactions on Cybernetics, 43: 898--909, 2013.

[7] Hong Chen, Yicong Zhou, Yuan-Yan Tang, Luoqing Li, Zhibin Pan. Convergence rate of semi-supervised greedy algorithm, Neural Networks, 44: 44--50, 2013.

[8]Hong Chen, Zhibin Pan, Luoqing Li, Yuan-Yan Tang. Error analysis of coefficient-based regularized classifier for density level detection, Neural Computation, 25: 1107-1121, 2013.

[9] Hong Chen. The convergence rate of a regularized ranking algorithm, Journal of Approximation Theory, 164: 1513--1519, 2012.

[10] Hong Chen, Luoqing Li, Jiangtao Peng. Semi-supervised learning based on high density regions estimation, Neural Networks, 23(7): 812--818, 2010.

[11] Hong Chen, Luoqing Li. Semi-supervised multi-category classification with Imperfect model, IEEE Transactions on Neural Networks, 20(10): 1594--1603, 2009.

顶会论文:

[1]Hong Chen, Xiaoqian Wang,Cheng Deng,Heng Huang, Group sparse additive machine, 31st Conference on Neural Information Processing Systems(NIPS), 2017.

[2] Xiaoqian Wang*,Hong Chen*,Dinggang Shen, Heng Huang, Regularized modal regression with applications in Cognitive Impairment Prediction , 31st Conference on Neural Information Processing Systems(NIPS), 2017.(* equal contribution)

[3] Hong Chen, Haifeng Xia, Wendong Cai,Heng Huang, Error Analysis of Generalized Nyström Kernel Regression, 30st Conference on Neural Information Processing Systems(NIPS), 2016.

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