In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables. More specifically, it quantifies the "amount of information" (in units such as bits) obtained about one random variable, through the other random variable. The concept of mutual information is intricately linked to that of entropy of a random variable, a fundamental notion in information theory, that defines the "amount of information" held in a random variable.
Mutual Information Lecture Notes and Tutorials PDF
– H(Y|C) is the entropy of class labels within each cluster, how do we calculate this?? Mutual Information tells us the reduction in the entropy of class labels that we ...
EE194 – Network Information Theory. Prof. Mai Vu. Lecture 1: Entropy and mutual information. 1 Introduction. Imagine two people Alice and Bob living in Toronto ...
This document is an introduction to entropy and mutual information for discrete random variables. It gives their definitions in terms of prob- abilities, and a few ...by EG Learned-Miller · 2013 · Cited by 14 · Related articles
Hardware Acceleration of Mutual Information-Based 3D Image Registration. Carlos R. ... ibility constraint, Lecture Notes in Computer Science 2208, 111. (2001).
Jun 28, 2016 — In order to build toward the concept of the standardized mutual information κ, we introduce first the definitions of Kullback-Leibler Divergence, ...
We review three prior information-theoretic measures of synergy and introduce a novel synergy measure defined as the difference between the whole and the ...
The method is based on a formulation of the mutual information between the model ... The final section of this chapter presents a tutorial application of EMMA.by PA Viola · 1995 · Cited by 4979 · Related articles
Here, we introduce an alternative formulation that replaces mutual information with entropy, which we call the deterministic information bottleneck (DIB), that we ...
Entropy. • Mutual Information. Dr. Yao Xie, ECE587, Information Theory, Duke University ... Useful to measure dependence of two random variables. H(X, Y ) = −.
their introduction, the past decade has seen a dramatic increase in the ... wise, we should calculate the mutual information between a spike train and an ...
wise known as pointwise mutual information (PMI), in a streaming context. ... and Pantel , introduced a probabilistic model for learning Shankian script-like ...by B Van Durme · Cited by 37 · Related articles
Alignment by Maximization of Mutual Information. International Journal of Computer Vision, 24(2) pg 137–154, 1997. Paul Viola and William M. Wells III. Artificial ...by P Viola · Cited by 4979 · Related articles
Index Terms: Fast spreading worms, Network anomaly detection,. Renyi mutual information. I. INTRODUCTION. Network monitoring systems have become a ...by Y Kopylova · Cited by 19 · Related articles
Lecture Notes 7: ... The following claim states that post-processing cannot increase the amount of information ... Lemma 2 (Information Processing Inequality).
Jul 1, 2015 — Also note that the problem considered in  is entirely different: They investigate pointwise mutual information. (PMI), a formalization of the ...by F Keller · Cited by 15 · Related articles
Chapter 2: Entropy and Mutual Information. University of Illinois at Chicago ECE 534, Fall 2009, Natasha Devroye. Chapter 2 outline. • Definitions. • Entropy.Missing: notes | Must include: notes
Feb 6, 2009 — normalized mutual information is proposed as a measure of re- dundancy ... tice because there is no clear guide on how to set this parameter.by PA Estévez · 2009 · Cited by 864 · Related articles
based on this principle using pointwise mutual information, and we show ... serve as a good objective guide for the development of boundary detection algo-.by P Isola · Cited by 147 · Related articles
Sep 30, 2018 — differential entropy and mutual information is presented as a signal progresses through a ... Makhoul, J. Linear prediction: A tutorial review.by J Gibson · 2018 · Cited by 14 · Related articles
Feb 20, 2003 — maximize the mutual information of the quantization. We show that ... Computers and Intractability: A Guide to the theory of NP-completeness.by B Mumey · 2003 · Cited by 23 · Related articles
Non-hierarchical information management ... mental model of the world and the system, depending on things ... Producers: Tagging of intelligence reports fairly.by C Mårtenson · Cited by 2 · Related articles
Jun 24, 2007 — Source: Xn. 1 → BRn. 1 → ̂Xn. 1. ▻ Channel: BRn. 1 → Xn. 1 → Yn. 1 → ̂BRn. 1. Sahai/Tatikonda (ISIT07). Feedback Tutorial. Jun 24, 2007.
Two examples of these kinds of interfaces are described. 1 Introduction. Information retrieval (IR) is hot. After 40 years of systematic research and develop- ment ...by G Marchionini · Cited by 35 · Related articles
resentations function like instructions to behave this way or that. However, ... The central quantity in information theory is called entropy. Entropy is a mea- sure of ...
✤ Information bottleneck and deep learning. ✤ Relationship hotly disputed. Need strong MI estimators! ✤ Conditional mutual information estimation. ✤ Plays vital ...