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FORTE
2008
15 years 8 months ago
Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning
Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in a...
Guoqiang Shu, Yating Hsu, David Lee
ACTAC
2006
126views more  ACTAC 2006»
15 years 6 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
NN
2006
Springer
15 years 6 months ago
Machine learning in soil classification
In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the cons...
Biswanath Bhattacharya, Dimitri P. Solomatine
GPEM
2002
104views more  GPEM 2002»
15 years 6 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
ICCV
2009
IEEE
16 years 11 months ago
Using machine learning to predict where people look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable o...
Tilke Judd, Krista Ehinger, Fr´edo Durand, Antoni...