4 search results - page 1 / 1 » Occam factors and model-independent Bayesian learning of con... |
95
Voted
CORR
2000
Springer
15 years 6 months ago
2000
Springer
193
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NIPS
2000
15 years 7 months ago
2000
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
181
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GECCO
2004
Springer
15 years 12 months ago
2004
Springer
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
222
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ESOP
2011
Springer
14 years 10 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...