3694 search results - page 161 / 739 » Stochastic complexity in learning |
TIT
1998
14 years 9 months ago
1998
We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
123
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UAI
1997
14 years 11 months ago
1997
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
ENTCS
2010
14 years 7 months ago
2010
Molecular biological models usually suffer from a dramatic combinatorial blow up. Indeed, proteins form complexes and can modify each others, which leads to the formation of a hug...
ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
108
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ICANN
2005
Springer
15 years 3 months ago
2005
Springer
Spike synchronisation and de-synchronisation are important for feature binding and separation at various levels in the visual system. We present a model of complex valued neuron ac...