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Rényi Divergence and Kullback-Leibler Divergence
- Source :
- IEEE Transactions on Information Theory. 60:3797-3820
- Publication Year :
- 2014
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2014.
-
Abstract
- R\'enyi divergence is related to R\'enyi entropy much like Kullback-Leibler divergence is related to Shannon's entropy, and comes up in many settings. It was introduced by R\'enyi as a measure of information that satisfies almost the same axioms as Kullback-Leibler divergence, and depends on a parameter that is called its order. In particular, the R\'enyi divergence of order 1 equals the Kullback-Leibler divergence. We review and extend the most important properties of R\'enyi divergence and Kullback-Leibler divergence, including convexity, continuity, limits of $\sigma$-algebras and the relation of the special order 0 to the Gaussian dichotomy and contiguity. We also show how to generalize the Pythagorean inequality to orders different from 1, and we extend the known equivalence between channel capacity and minimax redundancy to continuous channel inputs (for all orders) and present several other minimax results.<br />Comment: To appear in IEEE Transactions on Information Theory
- Subjects :
- Statistics::Theory
Kullback–Leibler divergence
Computer Science - Information Theory
Gaussian
Mathematics - Statistics Theory
02 engineering and technology
Physics::Data Analysis
Statistics and Probability
Library and Information Sciences
01 natural sciences
Convexity
Rényi entropy
Statistics::Machine Learning
010104 statistics & probability
Channel capacity
symbols.namesake
[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]
Statistics - Machine Learning
0202 electrical engineering, electronic engineering, information engineering
Statistics::Methodology
Entropy (information theory)
0101 mathematics
Axiom
Mathematics
Discrete mathematics
[MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT]
020206 networking & telecommunications
[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]
Minimax
Statistics::Computation
Computer Science Applications
[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT]
symbols
Information Systems
Subjects
Details
- ISSN :
- 15579654 and 00189448
- Volume :
- 60
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Information Theory
- Accession number :
- edsair.doi.dedup.....3774bdaf1a5e7f6a66ac3b797bd2dbfa