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AI
2002
Springer
15 years 7 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
KI
2007
Springer
15 years 7 months ago
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
Robert Moskovitch, Nir Nissim, Dima Stopel, Clint ...
199
Voted
IBERAMIA
2010
Springer
15 years 6 months ago
Dynamic Reward Shaping: Training a Robot by Voice
Reinforcement Learning is commonly used for learning tasks in robotics, however, traditional algorithms can take very long training times. Reward shaping has been recently used to ...
Ana C. Tenorio-Gonzalez, Eduardo F. Morales, Luis ...
266
Voted
MTA
2011
263views Hardware» more  MTA 2011»
15 years 2 months ago
Event detection and recognition for semantic annotation of video
Research on methods for detection and recognition of events and actions in videos is receiving an increasing attention from the scientific community, because of its relevance for ...
Lamberto Ballan, Marco Bertini, Alberto Del Bimbo,...
228
Voted
TWC
2010
15 years 2 months ago
Distributed Multicell-MISO Precoding Using the Layered Virtual SINR Framework
In this letter, we address the problem of distributed multi-antenna cooperative transmission in a cellular system. Most research in this area has so far assumed that base stations ...
Randa Zakhour, David Gesbert