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» Experimental Design for Variable Selection in Data Bases
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ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
16 years 10 days ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
DIS
2006
Springer
15 years 10 months ago
Model-Based Estimation of Word Saliency in Text
Abstract. We investigate a generative latent variable model for modelbased word saliency estimation for text modelling and classification. The estimation algorithm derived is able ...
Xin Wang, Ata Kabán
CIKM
2009
Springer
16 years 1 months ago
Incremental query evaluation for support vector machines
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
Danzhou Liu, Kien A. Hua
PVLDB
2010
175views more  PVLDB 2010»
15 years 5 months ago
Dynamic Join Optimization in Multi-Hop Wireless Sensor Networks
To enable smart environments and self-tuning data centers, we are developing the Aspen system for integrating physical sensor data, as well as stream data coming from machine logi...
Svilen R. Mihaylov, Marie Jacob, Zachary G. Ives, ...
TASLP
2008
101views more  TASLP 2008»
15 years 6 months ago
Speaker Identification Using Instantaneous Frequencies
This work presents an experimental evaluation of different features for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus, in a...
Marco Grimaldi, Fred Cummins