Amplifying Inter-Message Distance: On Information Divergence Measures in Big Data

Amplifying Inter-Message Distance: On Information Divergence Measures in Big Data

Message identification (M-I) divergence is an important measure of the information distance between probability distributions, similar to Kullback-Leibler (K-L) and Renyi divergence. In fact, M-I divergence with a variable parameter can make an effect on characterization of distinction between two d...

Full description

Bibliographic Details
Main Authors: Rui She, Shanyun Liu, Pingyi Fan
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Message identification (M-I) divergence
discrete distribution estimation
divergence estimation
big data analysis
outlier detection
Online Access:https://ieeexplore.ieee.org/document/8090523/

Internet

https://ieeexplore.ieee.org/document/8090523/

Similar Items