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第3期 张钢,等:面向大数据流的半监督在线多核学习算法 ·363. [J].Canadian Journal of Mathematics,1954,6(3):393- USA,2011:591-599. 404」 [17]FRANCESCO O,LUO Jie,BARBARA C.Multi kerel [7]GONEN M,ALPAYD E.Multiple kernel learning algo- learning with online-batch optimization[J].Joural of Ma- rithms [J].Journal of Machine Learning Research,2011 chine Learning Research,2012(13):227-253. (12):2211-2268. [18]STEVEN C H,RONG Jin,ZHAO Peilin,et al.Online [8 ORABONA F,JIE L,CAPUTO B.Multi kernel learning multiple kernel classification [J].Machine Learning, with online-batch optimization [J].Journal of Machine 2013,90(2):289-316. Learning Research,2012(13):227-253. [l9]UCI数据集:htp:/archive.ics.uci.edu/ml/[EB/OL]. [9]JIN R,HOI S C H,YANG T,et al.Online multiple kernel [2014-03-18]. learning:algorithms and mistake bounds[J].Algorithmic [20]YANG Haiqin,MICHAEL R L,IRWIN K.Efficient online Learning Theory,2010(6331):390-404. learning for multitask feature selection[J].ACM Transac- [10]QIN C,RUSU F.Scalable I/O-bound parallel incremental tions on Knowledge Discovery from Data,2013,7(2):6- gradient descent for big data analytics in GLADE[C]// 27. Proceedings of the Second Workshop on Data Analytics in [21]CHEN Jianhui,LIU Ji,YE Jieping.Learning incoherent the Cloud.New York,USA.2013:16-20. sparse and low-rank patterns from multiple tasks[J].ACM [11 SINDHWANI V,NIYOGI P,BELKIN M.Beyond the Transactions on Knowledge Discovery from Data,2012,5 point cloud:from transductive to semi-supervised learning (4):22-31. [C]//Proceedings of the 22nd International Conference [22]HONG Chaoqun,ZHU Jianke.Hypergraph-based multi-ex- on Machine Learning.Bonn,Germany,2005:824-831. ample ranking with sparse representation for transductive [12]李宏伟,刘扬,卢汉清,等.结合半监督核的高斯过程 learning image retrieval [J].Neurocomputing,2013 分[J].自动化学报,2009,35(7):888-895. (101):94-103. LI Hongwei,LIU Yang,LU Hanqing,et al.Gaussian [23]YU Jun,BIAN Wei,SONG Mingli,et al.Graph based processes classification combined with semi-supervised ker- transductive learning for cartoon correspondence construc- nels[J].Acta Automatica Sinica,2009,35(7):888-895. tion[J].Neurocomputing,2012(79):105-114. [13]邹恒明.计算机的心智:操作系统之哲学原理[M].北 作者简介: 京:机械工业出版社,2012:100-102. 张钢,男,1979年生,讲师,博士研 [14]BIFET A,HOLMES G,KIRKBY R,et al.MOA:massive 究生,CCF会员。主要研究方向为机器 online analysis[J].Journal of Machine Learning Research, 学习、数据挖掘和生物信息学,参与国 2010(11):1601-1604. 家自然科学基金项目1项,广东省自然 [15]KREMER H,KRANEN P,JANSEN T,et al.An effective 科学基金团队项目1项,获得软件著作 evaluation measure for clustering on evolving data streams 权2项,专利4项。发表学术论文40余 [C]//Proceedings of the 17th ACM SIGKDD International 篇,其中被SCI检索3篇,EI检索20余篇, Conference on Knowledge Discovery and Data Mining.San Diego,California,USA,2011:868-876. [16]BIFET A,HOLMES G,PFAHRINGER B,et al.Mining 谢晓珊,女,1990年生,硕士研究 frequent closed graphs on evolving data streams[C]//Pro- 生,发表学术论文3篇,主要研究方向 ceedings of the 17th ACM SIGKDD International Confer- 为机器学习、数据挖掘、模式识别和生 ence on Knowledge Discovery and Data Mining.San Diego, 物医学图像处理。[J]. Canadian Journal of Mathematics, 1954, 6(3): 393⁃ 404. [7] GONEN M, ALPAYD E. Multiple kernel learning algo⁃ rithms [ J]. Journal of Machine Learning Research, 2011 (12): 2211⁃2268. [ 8] ORABONA F, JIE L, CAPUTO B. Multi kernel learning with online⁃batch optimization [ J ]. Journal of Machine Learning Research, 2012(13): 227⁃253. [9]JIN R, HOI S C H, YANG T, et al. Online multiple kernel learning: algorithms and mistake bounds [ J]. Algorithmic Learning Theory, 2010(6331): 390⁃404. [10]QIN C, RUSU F. Scalable I/ O⁃bound parallel incremental gradient descent for big data analytics in GLADE [ C] / / Proceedings of the Second Workshop on Data Analytics in the Cloud. New York, USA, 2013: 16⁃20. [11] SINDHWANI V, NIYOGI P, BELKIN M. Beyond the point cloud: from transductive to semi⁃supervised learning [C] / / Proceedings of the 22nd International Conference on Machine Learning. Bonn, Germany, 2005: 824⁃831. [12]李宏伟, 刘扬, 卢汉清, 等. 结合半监督核的高斯过程 分[J]. 自动化学报, 2009, 35(7): 888⁃895. LI Hongwei, LIU Yang, LU Hanqing, et al. Gaussian processes classification combined with semi⁃supervised ker⁃ nels[J]. Acta Automatica Sinica, 2009, 35(7): 888⁃895. [13]邹恒明. 计算机的心智:操作系统之哲学原理[M]. 北 京: 机械工业出版社, 2012: 100⁃102. [14]BIFET A, HOLMES G, KIRKBY R, et al. MOA: massive online analysis[J]. Journal of Machine Learning Research, 2010(11): 1601⁃1604. [15]KREMER H, KRANEN P, JANSEN T, et al. An effective evaluation measure for clustering on evolving data streams [C] / / Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, 2011: 868⁃876. [16]BIFET A, HOLMES G, PFAHRINGER B, et al. Mining frequent closed graphs on evolving data streams[C] / / Pro⁃ ceedings of the 17th ACM SIGKDD International Confer⁃ ence on Knowledge Discovery and Data Mining. San Diego, USA, 2011: 591⁃599. [17] FRANCESCO O, LUO Jie, BARBARA C. Multi kernel learning with online⁃batch optimization[J]. Journal of Ma⁃ chine Learning Research, 2012(13): 227⁃253. [18] STEVEN C H, RONG Jin, ZHAO Peilin, et al. Online multiple kernel classification [ J ]. Machine Learning, 2013, 90(2): 289⁃316. [19]UCI 数据集:http: / / archive. ics. uci. edu / ml / [ EB/ OL]. [2014⁃03⁃18]. [20]YANG Haiqin, MICHAEL R L, IRWIN K. Efficient online learning for multitask feature selection[ J]. ACM Transac⁃ tions on Knowledge Discovery from Data, 2013, 7(2): 6⁃ 27. [21]CHEN Jianhui, LIU Ji, YE Jieping. Learning incoherent sparse and low⁃rank patterns from multiple tasks[J]. ACM Transactions on Knowledge Discovery from Data, 2012, 5 (4): 22⁃31. [22]HONG Chaoqun, ZHU Jianke. Hypergraph⁃based multi⁃ex⁃ ample ranking with sparse representation for transductive learning image retrieval [ J ]. Neurocomputing, 2013 (101): 94⁃103. [23] YU Jun, BIAN Wei, SONG Mingli, et al. Graph based transductive learning for cartoon correspondence construc⁃ tion[J]. Neurocomputing, 2012(79): 105⁃114. 作者简介: 张钢,男,1979 年生,讲师,博士研 究生,CCF 会员。 主要研究方向为机器 学习、数据挖掘和生物信息学,参与国 家自然科学基金项目 1 项 ,广东省自然 科学基金团队项目 1 项,获得软件著作 权 2 项,专利 4 项。 发表学术论文 40 余 篇,其中被 SCI 检索 3 篇,EI 检索 20 余篇, 谢晓珊,女,1990 年生,硕士研究 生,发表学术论文 3 篇,主要研究方向 为机器学习、数据挖掘、模式识别和生 物医学图像处理。 第 3 期 张钢,等:面向大数据流的半监督在线多核学习算法 ·363·
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