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ICML
2010
IEEE
15 years 5 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
15 years 10 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
163
Voted
WSDM
2010
ACM
160views Data Mining» more  WSDM 2010»
16 years 4 months ago
Learning Concept Importance Using a Weighted Dependence Model
Modeling query concepts through term dependencies has been shown to have a significant positive effect on retrieval performance, especially for tasks such as web search, where rel...
Michael Bendersky, Donald Metzler, W. Bruce Croft
IJIT
2004
15 years 8 months ago
Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...
BMCBI
2007
157views more  BMCBI 2007»
15 years 6 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...