3250 search results - page 100 / 650 » Parameterized Learning Complexity |
128
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KR
2004
Springer
15 years 7 months ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
112
Voted
CVPR
2006
IEEE
16 years 4 months ago
2006
IEEE
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image dat...
JMLR
2010
14 years 9 months ago
2010
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
123
Voted
ALT
2006
Springer
15 years 11 months ago
2006
Springer
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
132
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ICML
2006
IEEE
16 years 3 months ago
2006
IEEE
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...