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[...] Multi-Instance Learning. IEEE Transactions on Neural Networks and Learning Systems, in press. 2. X.-S. Wei, J. Wu and Z.-H. Zhou. Scalable Multi-Instance Learning. In: Proceedings of the 14th International Conference on Data Mining (ICDM’14), Shenzhen, China, 2014, pp.1037-1042. ATTN : This packages are free for academic usage. You can run them at your own risk. For other purposes, please contact Prof. Jianxin Wu (wujx2001@gmail.com). Requirement : To use this package, the Matlab version of Liblinear (http://www.csie.ntu.edu.tw/~cjlin/liblinear/) and the Matlab version of VLFeat [...]
[...] Arlington的Chris Ding教授访问LAMDA并作报告 2010-12-24 美国UT Austin的Huan Xu博士访问LAMDA并作报告 2010-12-06 周志华教授和黄圣君，王魏到温哥华参加NIPS'10会议 2010-12-02 厦门大学的王菡子教授访问LAMDA并作报告 2010-11-25 刘力平和眭俊明的硕士论文获得江苏省优秀硕士学位论文奖 [...]
[...] International conference on Machine Learning (ICML'13), Atlanta, GA, 2013, JMLR: W&CP 28(3), pp.906-914. [2] Wei Gao, Lu Wang, Rong Jin, Shenghou Zhu and Zhi-Hua Zhou. One-Pass AUC Optimzation. [...]
[...] (1) Bag generators with a dense sampling strategy perform better than those with other strategies; (2) The standard MIL assumption of learning algorithms is not suitable for image classification [...]
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[...] online streaming feature selection include (1) the continuous growth of feature volumes over time, (2) a large feature space, possibly of unknown or infinite size, and (3) the unavailability [...]