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AAAI
2008
14 years 11 days ago
2008
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
CORR
2011
Springer
13 years 5 months ago
2011
Springer
Modeling the behavior of imperfect agents from a small number of observations is a difficult, but important task. In the singleagent decision-theoretic setting, inverse optimal co...
ECML
2004
Springer
14 years 3 months ago
2004
Springer
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
NIPS
2001
13 years 11 months ago
2001
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
SIGMOD
2004
ACM
14 years 10 months ago
2004
ACM
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...