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NIPS
2004
13 years 8 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
NIPS
2001
13 years 8 months ago
Improvisation and Learning
This article presents a 2-phase computational learning model and application. As a demonstration, a system has been built, called CHIME for Computer Human Interacting Musical Enti...
Judy A. Franklin
IJCAI
1989
13 years 8 months ago
Reasoning about Kinematic Topology
t ion which is much more abstract than a place vocabulary, the kinematic topology. Kinematic topology does not define qualitative inference rules, but provides a characterization o...
Boi Faltings, Emmanuel Baechler, J. Primus
IJCAI
1989
13 years 8 months ago
Integrating Knowledge-Based System and Neural Network Techniques for Robotic Skill Acquisition
This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...
David Handelman, Stephen Lane, Jack Gelfand
WWW
2010
ACM
13 years 7 months ago
Mining advertiser-specific user behavior using adfactors
Consider an online ad campaign run by an advertiser. The ad serving companies that handle such campaigns record users' behavior that leads to impressions of campaign ads, as ...
Nikolay Archak, Vahab S. Mirrokni, S. Muthukrishna...
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