2934 search results - page 180 / 587 » Hypothesis Spaces for Learning |
173
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a gener...
230
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CVPR
2011
IEEE
14 years 10 months ago
2011
IEEE
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
180
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CIARP
2006
Springer
15 years 8 months ago
2006
Springer
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
215
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ETVC
2008
15 years 8 months ago
2008
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
198
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UAI
2000
15 years 7 months ago
2000
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...