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NIPS
2007
15 years 6 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
SIGIR
2012
ACM
13 years 7 months ago
Fighting against web spam: a novel propagation method based on click-through data
Combating Web spam is one of the greatest challenges for Web search engines. State-of-the-art anti-spam techniques focus mainly on detecting varieties of spam strategies, such as ...
Chao Wei, Yiqun Liu, Min Zhang, Shaoping Ma, Liyun...
ICDT
2009
ACM
166views Database» more  ICDT 2009»
16 years 5 months ago
A compositional framework for complex queries over uncertain data
The ability to flexibly compose confidence computation with the operations of relational algebra is an important feature of probabilistic database query languages. Computing confi...
Christoph Koch, Michaela Götz
ICMLA
2009
15 years 2 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
141
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CINQ
2004
Springer
133views Database» more  CINQ 2004»
15 years 8 months ago
Inductive Querying for Discovering Subgroups and Clusters
We introduce the problem of cluster-grouping and show that it integrates several important data mining tasks, i.e. subgroup discovery, mining correlated patterns and aspects from c...
Albrecht Zimmermann, Luc De Raedt