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陈洪
发布时间:2015-05-18

  

陈洪,教授,博士生导师。研究方向为机器学习、统计学习、逼近论。

2009.6博士毕业于湖北大学基础数学专业,湖北省优秀博士论文获得者。主持国家自然科学基金面上项目、青年基金等多项科研课题。主要从事新型学习算法设计、理论分析及应用研究,发表相关SCI论文30余篇,包括Appl. Comput. Harmon. Anal., J. Approx. Theory, IEEE TPAMI, IEEE TNNLS, IEEE T. Cybernetics, Neural Computation, Neural Networks, Bioinformatics等学术期刊,在机器学习顶级会议NIPS发表论文3篇。2016.3-2017.8在University of Texas at Arlington从事博士后研究,多次受邀请赴澳门大学、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、统计学基础及编程能力,有志于从事机器学习理论或应用领域的研究。

联系方式:chenh@mail.hzau.edu.cn

代表期刊论文:

[1]Yulong Wang, Yuan YanTang, Luoqing Li, Hong Chen,Jianjia Pan.Atomicrepresentation-basedclassification:theory,algorithm andapplications, IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI:10.1109/TPAMI.2017.2780094

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

[3]Xiaoqian Wang,Hong Chen, et al., Quantitative trait loci identification for brain endophenotypes via new additive model with random networks,Bioinformatics, 34(17): i866-i874.

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

[5]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.

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

[7]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.

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

[9]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.

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

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

[12]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 onNeural Information Processing Systems(NIPS), 2017.

[2]Xiaoqian Wang*,Hong Chen*,Dinggang Shen,Heng Huang,Regularizedmodalregressionwith applications inCognitive Impairment Prediction,31st Conference onNeural Information Processing Systems(NIPS), 2017.(* equal contribution)

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

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