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» Kernels for Multi--task Learning
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JMLR
2012
11 years 10 months ago
Algorithms for Learning Kernels Based on Centered Alignment
This paper presents new and effective algorithms for learning kernels. In particular, as shown by our empirical results, these algorithms consistently outperform the so-called uni...
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
COLT
2006
Springer
13 years 11 months ago
Mercer's Theorem, Feature Maps, and Smoothing
We study Mercer's theorem and feature maps for several positive definite kernels that are widely used in practice. The smoothing properties of these kernels will also be explo...
Ha Quang Minh, Partha Niyogi, Yuan Yao
CVPR
2012
IEEE
11 years 10 months ago
2D/3D rotation-invariant detection using equivariant filters and kernel weighted mapping
In many vision problems, rotation-invariant analysis is necessary or preferred. Popular solutions are mainly based on pose normalization or brute-force learning, neglecting the in...
Kun Liu, Qing Wang, Wolfgang Driever, Olaf Ronnebe...
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
14 years 1 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen