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136
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PODS
2002
ACM
167views Database» more  PODS 2002»
16 years 3 months ago
OLAP Dimension Constraints
In multidimensional data models intended for online analytic processing (OLAP), data are viewed as points in a multidimensional space. Each dimension has structure, described by a...
Carlos A. Hurtado, Alberto O. Mendelzon
127
Voted
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 3 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
JAIR
1998
198views more  JAIR 1998»
15 years 3 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
184
Voted
HICSS
1999
IEEE
152views Biometrics» more  HICSS 1999»
15 years 7 months ago
Incorporating Semantic Relationships into an Object-Oriented Database System
Semantic relationships, those class-to-class connections that carry inherent support for constraints and various other functionalities, play an important role when building inform...
Li-min Liu, Michael Halper
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 3 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