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·256· 智能系统学报 第17卷 ternational Joint Conference on Artificial Intelligence anced data[J].CAAI transactions on intelligent systems, Barcelona,Spain,2011:2355. 2020,15(3):520-527 [9]GENTILE C.A new approximate maximal margin classi- [16]MATHEW J,PANG C K,LUO Ming,et al.Classifica- fication algorithmfJ].Journal of machine learning re- tion of imbalanced data by oversampling in kernel space search.2001.2:213-242. of support vector machines[J].IEEE transactions on [10]CRAMMER K,DREDZE M,PEREIRA F.Confidence- neural networks and learning systems,2017,29(9):4065- weighted linear classification for text categorization[J]. 4076. The journal of machine learning research,2012,13(1): [17]CRAMMER K,DEKEL O,KESHET J,et al.Online 1891-1926. passive-aggressive algorithms[J].The journal of ma [11]王晓初,包芳,王士同,等基于最小最大概率机的迁 chine learning research,2006,7:551-585. 移学习分类算法[J].智能系统学报,2016,11(1): [18]VENKATESWARA H,EUSEBIO J.CHAKRABORTY 8492. S,et al.Deep hashing network for unsupervised domain WANG Xiaochu,BAO Fang,WANG Shitong,et al. adaptation[Cl//Proceedings of 2017 IEEE Conference on Transfer learning classification algorithms based on min- Computer Vision and Pattern Recognition.Honolulu, imax probability machine[J].CAAI transactions on intel- USA.2017:5385-5394. ligent systems,2016,11(1):84-92. [19]SAENKO K.KULIS B.FRITZ M,et al.Adapting visu- [12]ZHAO Peilin,HOI S C H.OTL:a framework of online al category models to new domains[C]//Proceedings of transfer learning[C]//Proceedings of the 27th Internation- the 11th European Conference on Computer Vision. al Conference on International Conference on Machine Heraklion,Greece,2010:213-226. Learning.Haifa,Israel:Omnipress,2010. 作者简介: [13]WU Qingyao,WU Hanrui,ZHOU Xiaoming,et al.On- 周晶雨,硕士研究生,主要研究方 line transfer learning with multiple homogeneous or het- 向为人工智能、模式识别。 erogeneous sources[J].IEEE transactions on knowledge and data engineering,2017,29(7):1494-1507. [14]CHAWLA N V,BOWYER K W,HALL L O,et al. SMOTE:synthetic minority over-sampling technique[J]. Journal of artificial intelligence research,2002,16: 321-357. 王士同,教授,博士生导师,主要 [15】左鹏玉,周洁,王土同.面对类别不平衡的增量在线序 研究方向为人工智能与模式识别。发 列极限学习机[J].智能系统学报,2020,15(3): 表学术论文近百篇。 520-527 ZUO Pengyu,ZHOU Jie,WANG Shitong.Incremental online sequential extreme learning machine for imbal-ternational Joint Conference on Artificial Intelligence. Barcelona, Spain, 2011: 2355. GENTILE C. A new approximate maximal margin classi￾fication algorithm[J]. Journal of machine learning re￾search, 2001, 2: 213–242. [9] CRAMMER K, DREDZE M, PEREIRA F. Confidence￾weighted linear classification for text categorization[J]. The journal of machine learning research, 2012, 13(1): 1891–1926. [10] 王晓初, 包芳, 王士同, 等. 基于最小最大概率机的迁 移学习分类算法 [J]. 智能系统学报, 2016, 11(1): 84–92. WANG Xiaochu, BAO Fang, WANG Shitong, et al. Transfer learning classification algorithms based on min￾imax probability machine[J]. CAAI transactions on intel￾ligent systems, 2016, 11(1): 84–92. [11] ZHAO Peilin, HOI S C H. OTL: a framework of online transfer learning[C]//Proceedings of the 27th Internation￾al Conference on International Conference on Machine Learning. Haifa, Israel: Omnipress, 2010. [12] WU Qingyao, WU Hanrui, ZHOU Xiaoming, et al. On￾line transfer learning with multiple homogeneous or het￾erogeneous sources[J]. IEEE transactions on knowledge and data engineering, 2017, 29(7): 1494–1507. [13] CHAWLA N V, BOWYER K W, HALL L O, et al. SMOTE: synthetic minority over-sampling technique[J]. Journal of artificial intelligence research, 2002, 16: 321–357. [14] 左鹏玉, 周洁, 王士同. 面对类别不平衡的增量在线序 列极限学习机 [J]. 智能系统学报, 2020, 15(3): 520–527. ZUO Pengyu, ZHOU Jie, WANG Shitong. Incremental online sequential extreme learning machine for imbal- [15] anced data[J]. CAAI transactions on intelligent systems, 2020, 15(3): 520–527. MATHEW J, PANG C K, LUO Ming, et al. Classifica￾tion of imbalanced data by oversampling in kernel space of support vector machines[J]. IEEE transactions on neural networks and learning systems, 2017, 29(9): 4065– 4076. [16] CRAMMER K, DEKEL O, KESHET J, et al. Online passive-aggressive algorithms[J]. The journal of ma￾chine learning research, 2006, 7: 551–585. [17] VENKATESWARA H, EUSEBIO J, CHAKRABORTY S, et al. Deep hashing network for unsupervised domain adaptation[C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, USA, 2017: 5385−5394. [18] SAENKO K, KULIS B, FRITZ M, et al. Adapting visu￾al category models to new domains[C]//Proceedings of the 11th European Conference on Computer Vision. Heraklion, Greece, 2010: 213−226. [19] 作者简介: 周晶雨,硕士研究生,主要研究方 向为人工智能、模式识别。 王士同,教授,博士生导师,主要 研究方向为人工智能与模式识别。发 表学术论文近百篇。 ·256· 智 能 系 统 学 报 第 17 卷
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