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CORR
2011
Springer
13 years 2 months ago
2011
Springer
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
INFOCOM
2005
IEEE
14 years 1 months ago
2005
IEEE
— We consider a scenario where a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
AMAI
2004
Springer
14 years 1 months ago
2004
Springer
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
PLDI
2010
ACM
14 years 27 days ago
2010
ACM
We present smooth interpretation, a method to systematically approximate numerical imperative programs by smooth mathematical functions. This approximation facilitates the use of ...