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PR
2010
156views more  PR 2010»
14 years 8 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
ICML
2010
IEEE
14 years 11 months ago
Simple and Efficient Multiple Kernel Learning by Group Lasso
We consider the problem of how to improve the efficiency of Multiple Kernel Learning (MKL). In literature, MKL is often solved by an alternating approach: (1) the minimization of ...
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Mic...
CE
2007
113views more  CE 2007»
14 years 9 months ago
Research and development of web-based virtual online classroom
To build a web-based virtual learning environment depends on information technologies, concerns technology supporting learning methods and theories. A web-based virtual online cla...
Zongkai Yang, Qingtang Liu
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 6 days ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
AAAI
2010
14 years 11 months ago
Smooth Optimization for Effective Multiple Kernel Learning
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...