Sciweavers

1799 search results - page 196 / 360
» Filtered Reinforcement Learning
Sort
View
CCS
2006
ACM
15 years 8 months ago
Can machine learning be secure?
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
CI
2005
106views more  CI 2005»
15 years 4 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird
ML
2006
ACM
132views Machine Learning» more  ML 2006»
15 years 4 months ago
A suffix tree approach to anti-spam email filtering
We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and...
Rajesh Pampapathi, Boris Mirkin, Mark Levene
ICASSP
2009
IEEE
15 years 11 months ago
A split quaternion nonlinear adaptive filter
A split quaternion learning algorithm for the training of nonlinear finite impulse response filters for the modelling of hypercomplex signals is proposed. A rigorous derivation ...
Bukhari Che Ujang, Clive Cheong Took, Alek Kavcic,...
HIS
2004
15 years 5 months ago
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
Chih-Chin Lai, Ming-Chi Tsai