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» Smooth Optimization for Effective Multiple Kernel Learning
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ICML
2006
IEEE
15 years 10 months ago
Deterministic annealing for semi-supervised kernel machines
An intuitive approach to utilizing unlabeled data in kernel-based classification algorithms is to simply treat unknown labels as additional optimization variables. For marginbased...
Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chape...
ICDM
2010
IEEE
187views Data Mining» more  ICDM 2010»
14 years 7 months ago
Financial Forecasting with Gompertz Multiple Kernel Learning
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...
Han Qin, Dejing Dou, Yue Fang
ICPR
2010
IEEE
15 years 29 days ago
Localized Multiple Kernel Regression
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
Mehmet Gönen, Ethem Alpaydin
CVPR
2008
IEEE
15 years 4 months ago
Fast kernel learning for spatial pyramid matching
Spatial pyramid matching (SPM) is a simple yet effective approach to compute similarity between images. Similarity kernels at different regions and scales are usually fused by som...
Junfeng He, Shih-Fu Chang, Lexing Xie
ICML
2008
IEEE
15 years 10 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye