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» Learning the Common Structure of Data
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BMCBI
2008
142views more  BMCBI 2008»
14 years 10 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
ICML
2007
IEEE
15 years 10 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
PAMI
2008
119views more  PAMI 2008»
14 years 9 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
ITRE
2005
IEEE
15 years 3 months ago
Structure learning of Bayesian networks using a semantic genetic algorithm-based approach
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
Sachin Shetty, Min Song
COLING
1996
14 years 11 months ago
Decision Tree Learning Algorithm with Structured Attributes: Application to Verbal Case Frame Acquisition
The Decision Tree Learning Algorithms (DTLAs) are getting keen attention from the natural language processing research comlnunity, and there have been a series of attempts to appl...
Hideki Tanaka