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教育经历 1985.101987.12英国牛津大学数学所计算数学博士 1978.101981.10吉林大学数学硕士 1974.101977.10吉林大学数学学士 工作经历 1998.10至今大连理工大学教师 1990.101998.10吉林大学教师 1988.11990.10英国巴斯大学博士后 1985.101987.12英国牛津大学数学所博士生 1981.101985.10吉林大学教师 1978.101981.10吉林大学硕士生 1977.101978.10辽宁省凌源县北方机械厂技术员 1969.91970.10牡丹江北方工具厂工人 1974.101977.10吉林大学本科生 1970.101974.10辽宁省凌源县北方机械厂工人 科研奖励 辽宁省教学成果一等奖 辽宁省科学技术奖 优秀教学成果奖(研究生类)

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Pan, Tingting,Zhao, Junhong,Wu, Wei,Yang, Jie.Learning imbalanced datasets based on SMOTE and Gaussian distribution[J],INFORMATION SCIENCES,2020,512:1214-1233 Zhao, Guoliang,Wu, Wei,Wang, Degang.Enhancement of the Variable Universe of Discourse Control By Hammersley Sequence-Based TP Model Transformation[A],2018,401-408 Li, Feng,Yang, Jie,Yao, Mingchen,Yang, Sibo,Wu, Wei.Extreme learning machine with local connections[J],NEUROCOMPUTING,2019,368:146-152 Zhao, Junhong,Shi, Maolin,Hu, Gang,Song, Xueguan,Zhang, Chao,Tao, Dacheng,Wu, Wei.A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data[J],IEEE ACCESS,2019,7:66703-66713 Yang, Sibo,Zhang, Chao,Wu, Wei.Binary Output Layer of Feedforward Neural Networks for Solving Multi-Class Classification Problems[J],IEEE ACCESS,2019,7:5085-5094 Alemu, Habtamu Zegeye,Zhao, Junhong,Li, Feng,Wu, Wei.Group L-1(/2) Regularization for Pruning Hidden Layer Nodes of Feedforward Neural Networks[J],IEEE ACCESS,2019,7:9540-9557 Li, Feng,Zurada, Jacek M.,Wu, Wei.Smooth group L-1/2 regularization for input layer of feedforward neural networks[J],NEUROCOMPUTING,2018,314:109-119 Li, Wenyu,Liu, Yan,Yang, Jie,Wu, Wei.A New Conjugate Gradient Method with Smoothing L-1/2 Regularization Based on a Modified Secant Equation for Training Neural Networks[J],NEURAL PROCESSING LETTERS,2018,48(2,SI):955-978 Alemu, Habtamu Zegeye,Wu, Wei,Zhao, Junhong.Feedforward Neural Networks with a Hidden Layer Regularization Method[J],SYMMETRY-BASEL,2018,10(10) Qu, Yanpeng,Shang, Changjing,Mac Parthalain, Neil,Wu, Wei,Shen, Qiang.Multi-functional nearest-neighbour classification[J],SOFT COMPUTING,2018,22(8):2717-2730 Li, Baohua,Lu, Huchuan,Li, Fu,Wu, Wei.Subspace Clustering With K-Support Norm[J],IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2018,28(2):302-313 Li, F.,Zurada, J. M.,Wu, W..SPARSE REPRESENTATION LEARNING OF DATA BY AUTOENCODERS WITH L-1/2 REGULARIZATION[J],NEURAL NETWORK WORLD,2018,28(2):133-147 赵国亮,吴微,汪德刚.Enhancement of the Variable Universe of Discourse Control By Hammersley Sequence-Based TP Model Transformation[A],8th International Conference on Information Science and Technology,2018,401-408 Zhao J.,Zurada J.M.,Yang J.,Wu W..The convergence analysis of SpikeProp algorithm with smoothing L1∕2 regularization.[J],Neural networks : the official journal of the International Neural Network Society,2018,103:19-28 吴微,卢湖川.Subspace Clustering under Complex Noise[J],IEEE Transactions on Circuits and Systems for Video Technology,2018,28:302-313 Fan, Yetian,Tang, Xiwei,Hu, Xiaohua,Wu, Wei,Ping, Qing.Prediction of essential proteins based on subcellular localization and gene expression correlation[J],BMC BIOINFORMATICS,2017,18(Suppl 13):470 Li, Feng,Zurada, Jacek M.,Liu, Yan,Wu, Wei.Input Layer Regularization of Multilayer Feedforward Neural Networks[J],IEEE ACCESS,2017,5:10979-10985 Li, Baohua,Wu, Wei.Subspace Clustering Under Multiplicative Noise Corruption[A],INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING, ISCIDE 2017,2017,10559:461-470 Fan, Yetian,Jiang, Xingpeng,Hu, Xiaohua,Song, Bo,Ling, Yuan,Wu, Wei.An Efficient Algorithm for Microbiome Sample Visualization Based on UniFrac Distance and Laplace Matrix[J],IEEE TRANSACTIONS ON NANOBIOSCIENCE,2016,15(4,SI):390-396 Fan, Qinwei,Wu, Wei,Zurada, Jacek M..Convergence of batch gradient learning with smoothing regularization and adaptive momentum for neural networks[J],SPRINGERPLUS,2016,5(1):295 吴微.Batch gradient metod for training of Pi-Sigma neural network with penalty[J],International Journal of Artificial Intelligence & Applications,2016,7(1):11-19 Yang, Dakun,Li, Zhengxue,Wu, Wei.Extreme learning machine for interval neural networks[J],NEURAL COMPUTING & APPLICATIONS,2016,27(1,SI):3-8 Fan, Yetian,Hu, Xiaohua,Tang, Xiwei,Ping, Qing,Wu, Wei.A novel algorithm for identifying essential proteins by integrating subcellular localization[A],IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM),2016,107-110 Fan, Yetian,Jiang, Xingpeng,Hu, Xiaohua,Song, Bo,Ling, Yuan,Wu, Wei.A novel dimensionality reduction algorithm based on Laplace matrix for microbiome data analysis[A],IEEE International Conference on Bioinformatics and Biomedicine,2015,49-54 Li W.,Wu W..A parameter conjugate gradient method based on secant equation for unconstrained optimization[J],Journal of Information and Computational Science,2015,12(16):5865-5871 Yang, Dakun,Li, Zhengxue,Liu, Yan,Zhang, Huisheng,Wu, Wei.A Modified Learning Algorithm for Interval Perceptrons with Interval Weights[J],NEURAL PROCESSING LETTERS,2015,42(2):381-396 Qu, Yanpeng,Shang, Changjing,Shen, Qiang,Mac Parthalain, Neil,Wu, Wei.Kernel-based Fuzzy-rough Nearest-neighbour Classification for Mammographic Risk Analysis[J],INTERNATIONAL JOURNAL OF FUZZY SYSTEMS,2015,17(3):471-483 Khan, Atlas,Xue, Li Zheng,Wei, Wu,Qu, YanPeng,Hussain, Amir,Vencio, Ricardo Z. N..Convergence Analysis of a New Self Organizing Map Based Optimization (SOMO) Algorithm[J],COGNITIVE COMPUTATION,2015,7(4):477-486 Liu, Yan,Li, Zhengxue,Yang, Dakun,Mohamed, Kh. Sh.,Wang, Jing,Wu, Wei.Convergence of batch gradient learning algorithm with smoothing L-1/2 regularization for Sigma-Pi-Sigma neural networks[J],NEUROCOMPUTING,2015,151(P1):333-341 龚燕,杨洁,吴微.基于蚁群迭代算法的近似测地线计算[J],大连理工大学学报,2015,55(1):115-118 吴微,杨洁.用于神经网络权值稀疏化的L1/2正则化方法[J],中国科学,2015,45(9):1487-1504 李正学,王兢,吴微.Convergence of batch gradient learning algorithm with smoothing L1/2 regularization for Sigma–Pi–Sigma neural networks[J],Neurocomputing,2015,151(1):333-341 Yao, Mingchen,Zhang, Chao,Wu, Wei.Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples[J],DISCRETE DYNAMICS IN NATURE AND SOCIETY,2015,2015 Fan, Yetian,Wu, Wei,Yang, Jie,Yang, Wenyu,Liu, Rongrong.An Algorithm for Motif Discovery with Iteration on Lengths of Motifs[J],IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,2015,12(1):136-141 吴微,杨洁.用于神经网络权值稀疏化的L_(1/2)正则化方法[J],中国科学. 数学,2015,45(9):1487-1504 Liu, Yan,Wu, Wei,Fan, Qinwei,Yang, Dakun,Wang, Jian.A modified gradient learning algorithm with smoothing L-1/2 regularization for Takagi-Sugeno fuzzy models[J],NEUROCOMPUTING,2014,138:229-237 Fan, Qinwei,Zurada, Jacek M.,Wu, Wei.Convergence of online gradient method for feedforward neural networks with smoothing L-1/2 regularization penalty[J],NEUROCOMPUTING,2014,131:208-216 Khan, Atlas,Yang, Jie,Wu, Wei.Double parallel feedforward neural network based on extreme learning machine with L-1/2 regularizer[J],International Workshop of Extreme Learning Machines (ELM),2014,128:113-118 Wu, Wei,Fan, Qinwei,Zurada, Jacek M.,Wang, Jian,Yang, Dakun,Liu, Yan.Batch gradient method with smoothing L-1/2 regularization for training of feedforward neural networks[J],NEURAL NETWORKS,2014,50:72-78 Fan, Ye-tian,Wu, Wei,Yang, Wen-yu,Fan, Qin-wei,Wang, Jian.A pruning algorithm with L (1/2) regularizer for extreme learning machine[J],JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS,2014,15(2):119-125 Yu, Ju-dong,Li, Feng,Wu, Wei,Wang, Jing.Neural Networks with L-1 Regularizer for Sparse Representation of Input Data[A],International Conference on Artificial Intelligence and Software Engineering (AISE),2014,437-440 吴微.A modified gradient learning algorithm with smoothing L1/2 regularization for Takagi-Sugeno fuzzy models[J],Neurocomputingv 138, p 229-37, 22 Aug. 2014,2014,138(4):229-237 吴微.Batch gradient method with smoothing L1/2 regularization for training of feedforward neural networks[J],Neural Networks,2014,50(1):72-78 吴微.Convergence of online gradient method for feedforward neural networks with smoothing L1/2 regularization penalty[J],Neurocomputing,2014,131(5):208-216 王兢,解永平,吴微.Identification of formaldehyde under different interfering gases conditions[A],2014 杨洁,吴微.Double parallel feedforward neural network based on extreme learning machine with L1/2regularizer[J],Neurocomputing,2014,128(March):113-118 杨洁,吴微.A Modified Gradient-Based Neuro-Fuzzy Learning Algorithm for Pi-Sigma Network Based on First-Order Takagi-Sugeno System[J],Journal of Mathematical Research with Applications,2014,34(1):114-126 余矩东,李锋,吴微,王健.Neural Networks with L1/2 Regularizer for Sparse Representation of Input Data[A],Proceedings of 2014 International Conference on Artificial Intelligence and Software Engineering (AISE2014), DEStech Publications,2014,437-440 Yang, Wenyu,Wu, Wei,Fan, Yetian,Li, Zhengxue.Particle Swarm Optimization Based on Local Attractors of Ordinary Differential Equation System[J],DISCRETE DYNAMICS IN NATURE AND SOCIETY,2014 Sun Q.,Liu Y.,Li Z.,Yang S.,Wu W.,Jin J..The binary output units of neural network[A],10th International Symposium on Neural Networks, ISNN 2013,2013,7951 LNCS(PART 1):250-257 Qu, Yanpeng,Shang, Changjing,Yang, Jie,Wu, Wei,Shen, Qiang.Modified gradient-based learning for local coupled feedforward neural networks with Gaussian basis function[J],NEURAL COMPUTING & APPLICATIONS,2013,22(SUPPL.1):S379-S394 Fan, Yetian,Wu, Wei,Liu, Rongrong,Yang, Wenyu.An iterative algorithm for motif discovery[A],17th Asia Pacific Symposium on Intelligent and Evolutionary Systems,2013,24:25-29 刘燕,杨洁,吴微,张会生.Convergence of online gradient methods for Pi-Sigma neural network with a penalty term, DOI: 10.1109/ANTHOLOGY.2013.[A],2013 IEEE Conference Anthology,2013,6784769-6784769 Qu, Yanpeng,Shen, Qiang,Mac Parthalain, Neil,Shang, Changjing,Wu, Wei.Fuzzy similarity-based nearest-neighbour classification as alternatives to their fuzzy-rough parallels[J],INTERNATIONAL JOURNAL OF APPROXIMATE REASONING,2013,54(1):184-195 Liu, Yan,Yang, Jie,Wu, Wei,Zhang, Huisheng.Convergence of online gradient methods for Pi-Sigma neural network with a penalty term[A],2013 IEEE Conference Anthology, ANTHOLOGY 2013,2013 Yang, Wenyu,Yang, Jie,Wu, Wei.A Modified Spiking Neuron that Involves Derivative of the State Function at Firing Time[J],NEURAL PROCESSING LETTERS,2012,36(2):135-144 Wang, Jian,Wu, Wei,Zurada, Jacek M..Computational properties and convergence analysis of BPNN for cyclic and almost cyclic learning with penalty[J],NEURAL NETWORKS,2012,33:127-135 Liu, Yan,Yang, Jie,Li, Long,Wu, Wei.Negative effects of sufficiently small initialweights on back-propagation neural networks[J],JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS,2012,13(8):585-592 Yang, Jie,Yang, Wenyu,Wu, Wei.A remark on the error-backpropagation learning algorithm for spiking neural networks[J],APPLIED MATHEMATICS LETTERS,2012,25(8):1118-1120 Zhang, Huisheng,Wu, Wei,Yao, Mingchen.Boundedness and convergence of batch back-propagation algorithm with penalty for feedforward neural networks[J],NEUROCOMPUTING,2012,89:141-146

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