This is an expository paper on the latest results in the theory of stochastic complexity and the associated MDL principle with special.
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This is an expository paper on the latest results in the theory of stochastic complexity and the associated MDL principle with special interest in modeling ...
Abstract: This is an expository paper on the latest results in the theory of stochastic complexity and the associated MDL principle.
From the perspective of coding theory, Rissanen developed a notion of stochastic model complexity, which builds upon Shannon's information criteria used for ...
This is an expository paper on the latest results in the theory of stochastic complexity and the associated MDL principle with special interest in modeling ...
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The stochastic complexity of a string of data, relative to a class of probabilistic models, is defined to be the fewest number of binary digits with which the ...
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Oct 10, 2022 · Abstract:We study the sample complexity of learning an \epsilon-optimal policy in the Stochastic Shortest Path (SSP) problem.
This is a minimum requirement for any kind of learning, for how can we find regular features in the data unless we can describe them! Unlike in the Bayesian ...
Jan 1, 2005 · This is an expository paper on the latest results in the theory of stochastic complexity and the associated MDL principle with special ...
The proposed criterion attempts to find data points which minimize the average Predictive Normalized Maximum Likelihood (pNML) on the unlabeled test set.