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» Mass estimation and its applications
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AMAI
2004
Springer
15 years 3 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
INFOCOM
2002
IEEE
15 years 2 months ago
Self-Verifying CSFQ
— Recently, a class of solutions including Core-Stateless Fair Queueing (CSFQ), Rainbow Fair Queueing, and Diffserv have been proposed to address the scalability concerns that ha...
Ion Stoica, Hui Zhang, Scott Shenker
ESANN
2008
14 years 11 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
SODA
2012
ACM
177views Algorithms» more  SODA 2012»
13 years 6 days ago
Stochastic coalescence in logarithmic time
The following distributed coalescence protocol was introduced by Dahlia Malkhi in 2006 motivated by applications in social networking. Initially there are n agents wishing to coal...
Po-Shen Loh, Eyal Lubetzky
CVPR
2003
IEEE
15 years 11 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...