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JMLR
2010
145views more  JMLR 2010»
14 years 11 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
JMLR
2010
185views more  JMLR 2010»
14 years 11 months ago
HMMPayl: an application of HMM to the analysis of the HTTP Payload
Zero-days attacks are one of the most dangerous threats against computer networks. These, by definition, are attacks never seen before. Thus, defense tools based on a database of ...
Davide Ariu, Giorgio Giacinto
JSAC
2010
146views more  JSAC 2010»
14 years 11 months ago
NLOS identification and mitigation for localization based on UWB experimental data
Abstract--Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwid...
Stefano Maranò, Wesley M. Gifford, Henk Wym...
PROMISE
2010
14 years 11 months ago
Replication of defect prediction studies: problems, pitfalls and recommendations
Background: The main goal of the PROMISE repository is to enable reproducible, and thus verifiable or refutable research. Over time, plenty of data sets became available, especial...
Thilo Mende
SAC
2010
ACM
14 years 11 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane
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