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NIPS
2007
13 years 10 months ago
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Ruslan Salakhutdinov, Geoffrey E. Hinton
PAMI
2008
144views more  PAMI 2008»
13 years 9 months ago
Twin Kernel Embedding
Visualization of non-vectorial objects is not easy in practice due to their lack of convenient vectorial representation. Representative approaches are Kernel PCA and Kernel Laplac...
Yi Guo, Junbin Gao, Paul W. Kwan
MMM
2009
Springer
186views Multimedia» more  MMM 2009»
14 years 3 months ago
A New Multiple Kernel Approach for Visual Concept Learning
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 2 months ago
Formulating context-dependent similarity functions
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a con...
Gang Wu, Edward Y. Chang, Navneet Panda
AIIA
2005
Springer
14 years 2 months ago
A Semantic Kernel to Exploit Linguistic Knowledge
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, th...
Roberto Basili, Marco Cammisa, Alessandro Moschitt...