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Joint entropy

In information theory, joint entropy is a measure of the uncertainty associated with a set of variables.
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Related topics

Related topics

20 relations
Chow–Liu treeConditional entropyConditional mutual informationCross entropy

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Are four eyes better than two? An examination of recent empirical evidence on the impact of joint audits
2013
2013
The Economics of Curiosity
We develop the hypothesis that an individual can get some value of information, even if they do not use the information for his… 
2012
2012
Entropy-based efficiency enhancement techniques for evolutionary algorithms
2009
2009
Joint Entropy Analysis Model for DDoS Attack Detection
Distributed Denial of service (DDoS) attack has become one of the most serious threats to the Internet. DDoS attack can be… 
2008
2008
A dropping proof of an entropy inequality
2004
2004
Analytical and numerical analysis of impact pulse parameters on consistency of drop impact results
JEDEC standard for board level drop test of handheld electronic products addresses test requirements in details. However, the… 
2004
2004
Unsupervised band selection for multispectral images using information theory
In this paper, the implication of the relations of information in the case of multispectral images is analyzed. Higher-order… 
Highly Cited
1995
Highly Cited
1995
On structure and stability in stochastic programs with random technology matrix and complete integer recourse
For two-stage stochastic programs with integrality constraints in the second stage, we study continuity properties of the… 
1988
1988
Allometric Estimation Of The Productivity Of Phytoplankton Assemblages
An allometric model is used to estimate the productivity of natural phytoplankton assemblages. The 14C fixation rates of > 5 ~m… 
1987
1987
Higher order probabilities
A number of writers have supposed that for the full specification of belief, higher order probabilities are required. Some have… 
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