Results 71 to 80 of about 255,284 (162)

On the symmetrized s-divergence

Open Mathematics, 2020
In this study, we work with the relative divergence of type s,s∈ℝs,s\in {\mathbb{R}}, which includes the Kullback-Leibler divergence and the Hellinger and χ 2 distances as particular cases.
Simić Slavko, Alzaid Sara Salem, Aydi Hassen   +2 more
doaj   +1 more source

A generalization of the Kullback–Leibler divergence and its properties [PDF]

Journal of Mathematical Physics, 2009
A generalized Kullback–Leibler relative entropy is introduced starting with the symmetric Jackson derivative of the generalized overlap between two probability distributions. The generalization retains much of the structure possessed by the original formulation.
openaire   +3 more sources

Efficient Distributional Reinforcement Learning with Kullback-Leibler Divergence Regularization

, 2022
In this article, we address the issues of stability and data-efficiency in reinforcement learning (RL). A novel RL approach, Kullback–Leibler divergence-regularized distributional RL (KLC51) is proposed to integrate the advantages of both stability in ...
Huiyun Li (12477580), Chunhua Zheng (12477571), Renxing Li (12477563), Yunduan Cui (12477513), Qing Liang (12477575), Zhiwei Shang (12477565)   +5 more
core   +1 more source

On Weighted Kullback–Leibler Divergence for Doubly Truncated Random Variables

Revstat Statistical Journal, 2019
In this communication, we study doubly truncated weighted Kullback–Leibler divergence (KLD) between two nonnegative random variables. The proposed measure is a generalization of the dynamic weighted KLD introduced by Yasaei Sekeh et al. (2013).
Rajesh Moharana , Suchandan Kayal
doaj   +1 more source

Unifying Computational Entropies via Kullback–Leibler Divergence [PDF]

, 2019
We introduce hardness in relative entropy, a new notion of hardness for search problems which on the one hand is satisfied by all one-way functions and on the other hand implies both next-block pseudoentropy and inaccessible entropy, two forms of computational entropy used in recent constructions of pseudorandom generators and statistically hiding ...
Rohit Agrawal 0002, Yi-Hsiu Chen, Thibaut Horel, Salil P. Vadhan   +3 more
openaire   +4 more sources

Efficient ECG classification based on the probabilistic Kullback-Leibler divergence

Informatics in Medicine Unlocked
Diagnostic systems of cardiac arrhythmias face early and accurate detection challenges due to the overlap of electrocardiogram (ECG) patterns. Additionally, these systems must manage a huge number of features.
Dhiah Al-Shammary, Mohammed Radhi, Ali Hakem AlSaeedi, Ahmed M. Mahdi, Ayman Ibaida, Khandakar Ahmed   +5 more
doaj   +1 more source

A Kullback-Leibler Divergence for Bayesian Model Diagnostics

Open Journal of Statistics, 2011
This paper considers a Kullback-Leibler distance (KLD) which is asymptotically equivalent to the KLD by Goutis and Robert [1] when the reference model (in comparison to a competing fitted model) is correctly specified and that certain regularity conditions hold true (ref. Akaike [2]).
Chen-Pin, Wang, Malay, Ghosh
openaire   +3 more sources

Evaluation of Kullback-Leibler Divergence

, 2015
Kullback-Leibler divergence is a leading measure of similarity or dissimilarity of probability distributions.
Homolová, Jitka
core  

Kullback-Leibler Divergence of Sleep-Wake Patterns Related with Depressive Severity in Patients with Epilepsy. [PDF]

Brain Sci, 2023
Liu M, Jiang J, Feng Y, Cai Y, Ding J, Wang X.   +5 more
europepmc   +1 more source

Kullback-Leibler Proximal Variational Inference [PDF]

We propose a new variational inference method based on a proximal framework that uses the Kullback-Leibler (KL) divergence as the proximal term. We make two contributions towards exploiting the geometry and structure of the variational bound. Firstly, we
Fua, Pascal, Khan, Mohammad Emtiyaz, Fleuret, François, Baqué, Pierre Bruno   +3 more
core   +1 more source