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» Temporal Difference Updating without a Learning Rate
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ASPLOS
2006
ACM
14 years 1 months ago
Temporal search: detecting hidden malware timebombs with virtual machines
Worms, viruses, and other malware can be ticking bombs counting down to a specific time, when they might, for example, delete files or download new instructions from a public we...
Jedidiah R. Crandall, Gary Wassermann, Daniela A. ...
JMLR
2006
153views more  JMLR 2006»
13 years 7 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
BC
2002
108views more  BC 2002»
13 years 7 months ago
Spike-timing-dependent plasticity: common themes and divergent vistas
Abstract. Recent experimental observations of spiketiming-dependent synaptic plasticity (STDP) have revitalized the study of synaptic learning rules. The most surprising aspect of ...
Ádám Kepecs, Mark C. W. van Rossum, ...
BMCBI
2007
133views more  BMCBI 2007»
13 years 7 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
FLAIRS
2008
13 years 9 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar