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Kullback–Leibler divergence

Known as: Kl-divergence, KL-distance, Kullback divergence 
In probability theory and information theory, the Kullback–Leibler divergence, also called discrimination information (the name preferred by Kullback… 
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Papers overview

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Review
2014
Review
2014
Rényi divergence is related to Rényi entropy much like Kullback-Leibler divergence is related to Shannon's entropy, and comes… 
Highly Cited
2012
Highly Cited
2012
In this paper we study distributionally robust optimization (DRO) problems where the ambiguity set of the probability… 
Highly Cited
2011
Highly Cited
2011
  • James M. Joyce
  • International Encyclopedia of Statistical Science
  • 2011
  • Corpus ID: 37718089
Highly Cited
2011
Highly Cited
2011
This letter describes algorithms for nonnegative matrix factorization (NMF) with the β-divergence (β-NMF). The β-divergence is a… 
Highly Cited
2010
Highly Cited
2010
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic… 
Highly Cited
2008
Highly Cited
2008
  • F. Pérez-Cruz
  • IEEE International Symposium on Information…
  • 2008
  • Corpus ID: 8811865
We present a method for estimating the KL divergence between continuous densities and we prove it converges almost surely… 
Highly Cited
2007
Highly Cited
2007
The Kullback Leibler (KL) divergence is a widely used tool in statistics and pattern recognition. The KL divergence between two… 
Highly Cited
2005
Highly Cited
2005
This paper presents a unifying view of messagepassing algorithms, as methods to approximate a complex Bayesian network by a… 
Highly Cited
2003
Highly Cited
2003
Over the last years significant efforts have been made to develop kernels that can be applied to sequence data such as DNA, text… 
Review
1991
Review
1991
Preface to the Second Edition. Preface to the First Edition. Acknowledgments for the Second Edition. Acknowledgments for the…