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» TRUST-TECH based Methods for Optimization and Learning
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ICML
2007
IEEE
16 years 4 months ago
Classifying matrices with a spectral regularization
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
Ryota Tomioka, Kazuyuki Aihara
ICCV
2005
IEEE
15 years 8 months ago
Learning Effective Image Metrics from Few Pairwise Examples
We present a new approach to learning image metrics. The main advantage of our method lies in a formulation that requires only a few pairwise examples. Apparently, based on the li...
Hwann-Tzong Chen, Tyng-Luh Liu, Chiou-Shann Fuh
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 7 months ago
Standard and averaging reinforcement learning in XCS
This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usu...
Pier Luca Lanzi, Daniele Loiacono
JMLR
2010
206views more  JMLR 2010»
14 years 10 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
ECCV
2006
Springer
16 years 5 months ago
Example Based Non-rigid Shape Detection
Since it is hard to handcraft the prior knowledge in a shape detection framework, machine learning methods are preferred to exploit the expert annotation of the target shape in a d...
Yefeng Zheng, Xiang Sean Zhou, Bogdan Georgescu, S...