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JMLR
2012
11 years 11 months ago
Contextual Bandit Learning with Predictable Rewards
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Alekh Agarwal, Miroslav Dudík, Satyen Kale,...
IJCNN
2000
IEEE
14 years 1 months ago
Applying CMAC-Based On-Line Learning to Intrusion Detection
The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existin...
James Cannady
BMCV
2000
Springer
14 years 1 months ago
Unsupervised Learning of Biologically Plausible Object Recognition Strategies
Recent psychological and neurological evidence suggests that biological object recognition is a process of matching sensed images to stored iconic memories. This paper presents a p...
Bruce A. Draper, Kyungim Baek
CORR
2002
Springer
100views Education» more  CORR 2002»
13 years 9 months ago
A neural model for multi-expert architectures
We present a generalization of conventional artificial neural networks that allows for a functional equivalence to multi-expert systems. The new model provides an architectural fr...
Marc Toussaint
CEC
2008
IEEE
13 years 11 months ago
Learning defect classifiers for visual inspection images by neuro-evolution using weakly labelled training data
This article presents results from experiments where a detector for defects in visual inspection images was learned from scratch by EANT2, a method for evolutionary reinforcement l...
Nils T. Siebel, Gerald Sommer