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  • 李武軍

    李武軍(南大教授)

    李武軍,博士,南京大學(xué)副教授,博士生導(dǎo)師。主要研究領(lǐng)域?yàn)槿斯ぶ悄堋C(jī)器學(xué)習(xí)、模式識(shí)別、數(shù)據(jù)挖掘、云計(jì)算與大數(shù)據(jù)。2003年畢業(yè)于南京大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)系,獲理學(xué)學(xué)士學(xué)位;2006年畢業(yè)于南京大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)系,獲工學(xué)碩士學(xué)位;2010年畢業(yè)于香港科技大學(xué)計(jì)算機(jī)科學(xué)與工程系,獲工學(xué)博士學(xué)位。


    個(gè)人經(jīng)歷

    李武軍,博士,副教授,博士生導(dǎo)師。主要研究領(lǐng)域?yàn)槿斯ぶ悄、機(jī)器學(xué)習(xí)、模式識(shí)別、數(shù)據(jù)挖掘、云計(jì)算與大數(shù)據(jù)。2003年畢業(yè)于南京大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)系,獲理學(xué)學(xué)士學(xué)位;2006年畢業(yè)于南京大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)系,獲工學(xué)碩士學(xué)位;2010年畢業(yè)于香港科技大學(xué)計(jì)算機(jī)科學(xué)與工程系,獲工學(xué)博士學(xué)位。

    2010年9月至2013年12月于上海交通大學(xué)計(jì)算機(jī)科學(xué)與工程系從事教學(xué)與科研工作。2014年1月加入南京大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)系。曾獲Google獎(jiǎng)教金、南京大學(xué)登峰人才支持計(jì)劃(B層次)。發(fā)表論文30余篇,其中大部分發(fā)表在Artificial Intelligence、IEEE Transactions TKDE、ICML、NIPS、SIGIR、IJCAI、AAAI等國(guó)際知名期刊和會(huì)議上,F(xiàn)任《Frontiers of Computer Science》青年副編輯,擔(dān)任TPAMI、TNNLS、TKDE、TPDS、TCSVT、中國(guó)科學(xué)、科學(xué)通報(bào)、軟件學(xué)報(bào)等多個(gè)國(guó)際和國(guó)內(nèi)知名期刊的特邀評(píng)審人,并擔(dān)任ICML、NIPS、IJCAI、UAI等多個(gè)國(guó)際知名會(huì)議的程序委員或者評(píng)審人。主持和參加了多項(xiàng)國(guó)家級(jí)課題研究,包括國(guó)家自然科學(xué)基金項(xiàng)目、863重大項(xiàng)目等。

    指導(dǎo)的學(xué)生在AAAI、IJCAI、NIPS、SIGIR等國(guó)際知名會(huì)議上發(fā)表多篇高水平論文,繼續(xù)深造的學(xué)生獲得斯坦福大學(xué)、威斯康辛-麥迪遜分校、南加州大學(xué)、香港科技大學(xué)等知名高校的博士全額獎(jiǎng)學(xué)金,就業(yè)的學(xué)生被微軟美國(guó)總部、摩根斯坦利、阿里巴巴、騰訊等知名企業(yè)聘用。

    2010年9月至2013年12月于上海交通大學(xué)計(jì)算機(jī)科學(xué)與工程系從事教學(xué)與科研工作。

    2014年1月加入南京大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)系機(jī)器學(xué)習(xí)與數(shù)據(jù)挖掘組,入選南京大學(xué)登峰人才支持計(jì)劃(B層次)

    李武軍

    研究方向

    主要研究領(lǐng)域?yàn)槿斯ぶ悄、機(jī)器學(xué)習(xí)、模式識(shí)別、數(shù)據(jù)挖掘、云計(jì)算與大數(shù)據(jù)。

    主要成績(jī)

    Conference/Workshop organization:

    orkshop onMachine Learning in China (MLChina’14)

    PC member:

    2015: IJCAI (Senior PC),AAAI,SIGKDD,UAI, PAKDD,BigComp
    2014: ICML, NIPS (reviewer), UAI, SDM, ICPR, ICTAI, BigComp, CCDM, CCPR, PRICAI, CIDM, NLPCC, CCF-BigData
    2013: IJCAI
    2012: ICTAI
    2011: IJCAI, ICTAI, ICONIP
    2010: ICPR

    Editorial board member:

    Communications of the China Computer Federation (CCCF)
    Junior Associate Editor of Frontiers of Computer Science(FCS)

    Journal reviewer:

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    IEEE Transactions on Neural Networks and Learning Systems
    IEEE Transactions on Knowledge and Data Engineering
    IEEE Transactions on Parallel and Distributed Systems
    IEEE Transactions on Circuits and Systems for Video Technology
    ACM Transactions on Intelligent Systems and Technology
    Data Mining and Knowledge Discovery
    Pattern Recognition
    Neural Networks
    Neurocomputing
    Frontiers of Computer Science
    Journal of Computer Science and Technology
    SCIENCE CHINA Information Sciences
    Chinese Science Bulletin
    Journal of Software

    Selected Publications

    (* indicates students under my supervision)

    Papers:

      Learning to hash for big data: current status and future trends.
      Wu-Jun Li, Zhi-Hua Zhou.
      To Appear in Chinese Science Bulletin (In Chinese, Invited Paper).Relational collaborative topic regression for recommender systems.
      Hao Wang*,Wu-Jun Li.
      To Appear in IEEE Transactions on Knowledge and Data Engineering (TKDE).Multicategory large margin classification methods: hinge losses vs. coherence functions.
      Zhihua Zhang, Cheng Chen, Guang Dai,Wu-Jun Li, Dit-Yan Yeung.
      Artificial Intelligence,215: 55-78, 2014.Distributed Power-law Graph Computing: Theoretical and Empirical Analysis.
      Cong Xie*, Ling Yan*,Wu-Jun Li, Zhihua Zhang.
      Proceedings ofthe28thAnnual Conference on Neural Information Processing Systems (NIPS),2014.

      Distributed Stochastic ADMM for Matrix Factorization.
      Zhi-Qin Yu*, Xing-Jian Shi*, Ling Yan*,Wu-Jun Li.
      Proceedings ofthe23rdACMInternationalConferenceonInformationandKnowledgeManagement (CIKM),2014.Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising.
      Ling Yan*,Wu-Jun Li, Gui-Rong Xue, Dingyi Han.
      Proceedings of the31stInternational Conference on Machine Learning(ICML),2014.Supervised Hashing with Latent Factor Models.
      Peichao Zhang*, Wei Zhang*,Wu-Jun Li, Minyi Guo.
      Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR),2014.Large-Scale Supervised Multimodal Hashing with Semantic Correlation Maximization.
      Dongqing Zhang*,Wu-Jun Li.
      Proceedings of theTwenty-Eighth AAAI Conference on Artificial Intelligence (AAAI),2014.Robust crowdsourced learning.
      Zhiquan Liu*, Luo Luo*,Wu-Jun Li.
      Proceedings of theIEEE International Conference on Big Data (BigData),2013.

      Online Egocentric models for citation networks.
      Hao Wang*,Wu-Jun Li.
      Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI),2013.Collaborative topic regression with social regularization for tag recommendation.
      Hao Wang*, Binyi Chen*,Wu-Jun Li.
      Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI),2013.Isotropic hashing.
      Weihao Kong*,Wu-Jun Li.
      Proceedings of the 26thAnnual Conference on Neural Information Processing Systems (NIPS),2012.Manhattan hashing for large-scale image retrieval.
      Weihao Kong*,Wu-Jun Li, Minyi Guo.
      Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR),2012.Double-bit quantization for hashing.
      Weihao Kong*,Wu-Jun Li.
      Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI),2012.Emoticon smoothed language models for Twitter sentiment analysis.
      Kun-Lin Liu*,Wu-Jun Li, Minyi Guo.
      Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI),2012.Sparse probabilistic relational projection.
      Wu-Jun Li, Dit-Yan Yeung.
      Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI),2012.Social relations model for collaborative filtering.
      Wu-Jun Li, Dit-Yan Yeung.
      Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI),2011.Generalized latent factor models for social network analysis.
      Wu-Jun Li, Dit-Yan Yeung, Zhihua Zhang.
      Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI), 2011.MILD: Multiple-instance learning via disambiguation.
      Wu-Jun Li, Dit-Yan Yeung.
      IEEE Transactions on Knowledge and Data Engineering (TKDE), 22 (1): 76-89, 2010.Gaussian process latent random field.
      Guoqiang Zhong,Wu-Jun Li, Dit-Yan Yeung, Cheng-Lin Liu, Xinwen Hou.
      Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI),2010.Probabilistic relational PCA.
      Wu-Jun Li, Dit-Yan Yeung, Zhihua Zhang.
      Proceedings of theTwenty-Third Annual Conference on Neural Information Processing Systems (NIPS), 2009.Relation regularized matrix factorization.
      Wu-Jun Li, Dit-Yan Yeung.
      Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI), 2009.Localized content-based image retrieval through evidence region identification.
      Wu-Jun Li, Dit-Yan Yeung.
      Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2009.TagiCoFi: Tag informed collaborative filtering.
      Yi Zhen,Wu-Jun Li, Dit-Yan Yeung.
      Proceedings of the Third ACM Conference on Recommender Systems (RecSys), 2009.Latent Wishart processes for relational kernel learning.
      Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung.
      Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS),JMLR: W&CP 5, pp. 336-343, 2009.Coherence functions for multicategory margin-based classification methods.
      Zhihua Zhang, Michael Jordan,Wu-Jun Li, Dit-Yan Yeung.
      Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS),JMLR: W&CP 5, pp. 647-654, 2009.Joint boosting feature selection for robust face recognition.
      Rong Xiao,Wu-Jun Li, Yuandong Tian, Xiaoou Tang.
      Proceedings of theIEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR)(2):1415-1422, 2006.

    Book (in Chinese):

      周憬宇,李武軍,過敏意.《飛天開放平臺(tái)編程指南-阿里云計(jì)算的實(shí)踐》. 電子工業(yè)出版社,2013年3月.

    演講

    Dec 2014. Big Data Machine Learning. Ocean University of China.Nov 2014. Learning to Hash for Big Data. University of Electronic Science and Technology of China.Nov 2014. Big Data Machine Learning. Sichuan University.Nov 2014. Big Data Machine Learning. Nanjing University of Information Science and Technology.Nov 2014. Big Data Machine Learning. XI’AN University of Technology.Nov 2014. Big Data Machine Learning.China Workshop on Machine Learning and Applications.Nov 2014. Learning to Hash for Big Data. Tutorial at CIKM 2014 .Oct 2014.Big Data Machine Learning.Youth Academic Forum.National Key Laboratory for Novel Software Technology,Nanjing University.May2014. Learning to Hash for Big Data.Young Scientist Forum on Big Data and Mobile Internet.Organized by China Association for Science and Technology.May 2014. Learning to Hash for Big Data. Zhejiang Normal University.Dec 2013. Learning to Hash for Big Data Retrieval and Mining.Key Lab of Intelligent Information Processing, CAS.Dec 2013. Big Data Machine Learning. Huazhong University of Science and Technology.Nov 2013. Learning to Hash for Big Data Retrieval and Mining. Shandong University, Invited by YOCSEF Jinan.Nov 2013. Learning to Hash for Big Data Retrieval and Mining.Forum on Big Data Machine Learning, Tianjin University, Invited by YOCSEF Tianjin.May 2013. Big Data Machine Learning. BesTV, Shanghai.Jan 2013. Learning to Hash for Big Data Retrieval and Mining.The Workshop on Data Science and Information Industry. Shanghai Jiao Tong University.

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