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» Learning programs from noisy data
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ICNC
2005
Springer
15 years 8 months ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
NIPS
2007
15 years 3 months ago
Bayesian Co-Training
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...
Shipeng Yu, Balaji Krishnapuram, Rómer Rosa...
SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 2 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
AAAI
2007
15 years 4 months ago
Kernel Regression with Order Preferences
We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value...
Xiaojin Zhu, Andrew B. Goldberg
SIGSOFT
2005
ACM
16 years 3 months ago
Applying classification techniques to remotely-collected program execution data
There is an increasing interest in techniques that support measurement and analysis of fielded software systems. One of the main goals of these techniques is to better understand ...
Murali Haran, Alan F. Karr, Alessandro Orso, Adam ...