This paper proposes a stratified regularity measure: a novel entropic measure to describe data regularity as a function of data domain stratification.
This paper proposes a stratified regularity measure: a novel entropic measure to describe data regularity as a function of data domain stratification.
This paper proposes a stratified regularity measure: a novel entropic measure to describe data regularity as a function of data domain stratification.
関連する質問
When to use Jensen-Shannon divergence?
What are the applications of Jensen-Shannon divergence?
What is the Jensen-Shannon divergence equation?
What is the Jensen-Shannon algorithm?
The square root of the Jensen–Shannon divergence is a metric often referred to as Jensen–Shannon distance. The similarity between the distributions is greater ...
含まれない: Stratified | 必須にする:Stratified
In this study, we evaluated the use of the Kullback-Leibler divergence (DKL), the Jensen-Shannon divergence (DJS), the Jenson-Shannon distance (DistJS), and the ...
Researchr is a web site for finding, collecting, sharing, and reviewing scientific publications, for researchers by researchers. Sign up for an account to ...
We introduce novel approaches to active learning based on the algorithms Bootstrap- LV and ACTIVEDECORATE, by using Jensen-Shannon divergence (a similarity ...
In the Early Lung Cancer Action Project (ELCAP), we found not only solid but also part-solid and nonsolid nodules in patients at both baseline and repeat CT ...
2024/03/07 · The Jensen-Shannon divergence is used to measure the similarity between two probability distributions, particularly in the field of Machine Learning.
含まれない: Stratified | 必須にする:Stratified
Stratified regularity measures with Jensen-Shannon divergence. K. Okada, S. Periaswamy, и J. Bi. CVPR Workshops, стр. 1-8. IEEE Computer Society, (2008 ) ...