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On an Approximation of Mutual Information

IEEE Transactions on Computers, 1974
An approximation of mutual information which is often used for feature evaluation in pattern recognition is shown to be more closely related to Bayes error probability than mutual information is when equal a priori probabilities are assumed.
openaire   +3 more sources

Information acquisition and mutual funds

Journal of Economic Theory, 2004
We explain the size and the existence of the mutual fund industry by generalizing the standard competitive noisy rational expectations framework with endogenous information acquisition. Since informed agents optimally choose to open mutual funds in order to sell their private information, mutual funds are an endogenous feature of our equilibrium.
Diego GarcĂ­a, Joel M. Vanden
openaire   +1 more source

On causality and mutual information

2008 47th IEEE Conference on Decision and Control, 2008
We provide for the first time a formulation of non-linear, nonstationary causality in terms of mutual information. We provide two fundamental mutual information identities; the first relating Granger type causality to Sims type causality. The second providing a decomposition of mutual information into a sum of Granger and Sims type terms.
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Ensemble estimation of mutual information

2017 IEEE International Symposium on Information Theory (ISIT), 2017
We derive the mean squared error convergence rates of kernel density-based plug-in estimators of mutual information measures between two multidimensional random variables X and Y for two cases: 1) X and Y are both continuous; 2) X is continuous and Y is discrete.
Kevin R. Moon   +2 more
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Mutual Information, Fisher Information, and Efficient Coding

Neural Computation, 2016
Fisher information is generally believed to represent a lower bound on mutual information (Brunel & Nadal, 1998 ), a result that is frequently used in the assessment of neural coding efficiency. However, we demonstrate that the relation between these two quantities is more nuanced than previously thought.
Xue-Xin Wei, Alan A. Stocker
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Mutual Information and Categorical Perception

Psychological Science, 2021
Categorical perception refers to the enhancement of perceptual sensitivity near category boundaries, generally along dimensions that are informative about category membership. However, it remains unclear exactly which dimensions are treated as informative and why.
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Shuffle crossover and mutual information

Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), 2003
We introduce a crossover operator that is not dependent on the initial layout of the genome. While maintaining a low positional bias, the MISC (mutual information and shuffle crossover) algorithm is competitive with one-point crossover and works by automatically regrouping bits that are considered to be interdependent.
openaire   +1 more source

Transaction Costs, Portfolio Characteristics, and Mutual Fund Performance

Management Science, 2021
Yuehua Tang   +2 more
exaly  

Using mutual information for selecting features in supervised neural net learning

IEEE Transactions on Neural Networks, 1994
Roberto Battiti
exaly  

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