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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
WWW
2010
ACM
14 years 2 months ago
Sampling community structure
We propose a novel method, based on concepts from expander graphs, to sample communities in networks. We show that our sampling method, unlike previous techniques, produces subgra...
Arun S. Maiya, Tanya Y. Berger-Wolf
CSDA
2008
128views more  CSDA 2008»
13 years 8 months ago
Classification tree analysis using TARGET
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
J. Brian Gray, Guangzhe Fan
EOR
2006
135views more  EOR 2006»
13 years 7 months ago
Principles of scatter search
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first propose...
Rafael Martí, Manuel Laguna, Fred Glover
CVPR
2008
IEEE
14 years 10 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell