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158
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ICML
2004
IEEE
15 years 10 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
ITICSE
2004
ACM
15 years 10 months ago
Generation as method for explorative learning in computer science education
The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advant...
Andreas Kerren
131
Voted
SIGECOM
2004
ACM
135views ECommerce» more  SIGECOM 2004»
15 years 10 months ago
Applying learning algorithms to preference elicitation
We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that l...
Sébastien Lahaie, David C. Parkes
148
Voted
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 8 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
ATAL
2006
Springer
15 years 6 months ago
Selecting informative actions improves cooperative multiagent learning
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
Liviu Panait, Sean Luke