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» Parameterized Learning Complexity
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ICML
2004
IEEE
14 years 10 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
CIE
2008
Springer
13 years 10 months ago
First-Order Model Checking Problems Parameterized by the Model
We study the complexity of the model checking problem, for fixed models A, over certain fragments L of first-order logic, obtained by restricting which of the quantifiers and boole...
Barnaby Martin
ICDCS
2007
IEEE
14 years 4 months ago
Testing Security Properties of Protocol Implementations - a Machine Learning Based Approach
Security and reliability of network protocol implementations are essential for communication services. Most of the approaches for verifying security and reliability, such as forma...
Guoqiang Shu, David Lee
JMLR
2006
134views more  JMLR 2006»
13 years 9 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz