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"Reinforcement learning is learning what to do how to map situations to actions so as to maximize a numerical reward signal. The learner is not told which actions to take, as ...
VIS
2009
IEEE
14 years 10 months ago
2009
IEEE
In this poster, we present how our previously published method of computing continuous 2D scatterplots can be performed with hardware acceleration on a GPU. By doing this, we expl...
CHI
2008
ACM
14 years 9 months ago
2008
ACM
Most research on how people represent procedures suggests that control labels are central. However, our data suggest that even moderately-experienced users do not rely on labels t...
STOC
2001
ACM
14 years 9 months ago
2001
ACM
We show how to bound the mixing time and log-Sobolev constants of Markov chains by bounding the edge-isoperimetry of their underlying graphs. To do this we use two recent techniqu...
PERCOM
2004
ACM
14 years 8 months ago
2004
ACM
This paper introduces and solves a security problem of pervasive computing: how to define authorizations for offline interactions when trust relationships among entities do not ex...