451 search results - page 26 / 91 » Learning conditional preference networks |
UAI
2003
13 years 9 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
JMLR
2010
13 years 2 months ago
2010
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
ROMAN
2007
IEEE
14 years 1 months ago
2007
IEEE
—This paper proposes a novel method of learning a users preferred reward modalities for human-robot interaction through solving a cooperative training task. A learning algorithm ...
CIDM
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
AIR
2006
13 years 7 months ago
2006
Abstract. An over-zealous machine learner can automatically generate large, intricate, theories which can be hard to understand. However, such intricate learning is not necessary i...