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ISSTA
2012
ACM
13 years 8 months ago
A quantitative study of accuracy in system call-based malware detection
Over the last decade, there has been a significant increase in the number and sophistication of malware-related attacks and infections. Many detection techniques have been propos...
Davide Canali, Andrea Lanzi, Davide Balzarotti, Ch...
ICML
2008
IEEE
16 years 7 months ago
Non-parametric policy gradients: a unified treatment of propositional and relational domains
Policy gradient approaches are a powerful instrument for learning how to interact with the environment. Existing approaches have focused on propositional and continuous domains on...
Kristian Kersting, Kurt Driessens
UAI
2003
15 years 7 months ago
Locally Weighted Naive Bayes
Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by thes...
Eibe Frank, Mark Hall, Bernhard Pfahringer
ICML
2009
IEEE
16 years 7 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
ICML
2004
IEEE
16 years 7 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...