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» Inferring Hidden Causal Structure
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KDD
2009
ACM
172views Data Mining» more  KDD 2009»
14 years 3 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
JCB
2006
129views more  JCB 2006»
13 years 11 months ago
GenRate: A Generative Model that Reveals Novel Transcripts in Genome-Tiling Microarray Data
Genome-wide microarray designs containing millions to hundreds of millions of probes are available for a variety of mammals, including mouse and human. These genome tiling arrays ...
Brendan J. Frey, Quaid Morris, Timothy R. Hughes
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
14 years 11 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
ICFP
2007
ACM
14 years 11 months ago
Implicit phasing for R6RS libraries
The forthcoming Revised6 Report on Scheme differs from previous reports in that the language it describes is structured as a set of libraries. It also provides a syntax for defini...
Abdulaziz Ghuloum, R. Kent Dybvig
CSE
2009
IEEE
14 years 5 months ago
Collaborative Mining in Multiple Social Networks Data for Criminal Group Discovery
—The hidden knowledge in social networks data can be regarded as an important resource for criminal investigations which can help finding the structure and organization of a crim...
Amin Milani Fard, Martin Ester