Mutual Information Lecture Notes and Tutorials PDF Download

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

Normalized Mutual Information

Normalized Mutual Information

– 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 ...
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Entropy and mutual information

Entropy and mutual information

EE194 – Network Information Theory. Prof. Mai Vu. Lecture 1: Entropy and mutual information. 1 Introduction. Imagine two people Alice and Bob living in Toronto ...
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Entropy and Mutual Information

Entropy and Mutual Information

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
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Mutual Information (Castro-Pareja)

Mutual Information (Castro-Pareja)

Hardware Acceleration of Mutual Information-Based 3D Image Registration. Carlos R. ... ibility constraint, Lecture Notes in Computer Science 2208, 111. (2001).
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Estimation of Standardized Mutual Information

Estimation of Standardized Mutual Information

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, ...
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Quantifying Synergistic Mutual Information

Quantifying Synergistic Mutual Information

We review three prior information-theoretic measures of synergy and introduce a novel synergy measure defined as the difference between the whole and the ...
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Alignment by Maximization of Mutual Information

Alignment by Maximization of Mutual Information

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
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optimization of mutual information in learning

optimization of mutual information in learning

Here, we introduce an alternative formulation that replaces mutual information with entropy, which we call the deterministic information bottleneck (DIB), that we ...
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Lecture 2: Entropy and Mutual Information

Lecture 2: Entropy and Mutual Information

Entropy. • Mutual Information. Dr. Yao Xie, ECE587, Information Theory, Duke University ... Useful to measure dependence of two random variables. H(X, Y ) = −.
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Estimation of Entropy and Mutual Information

Estimation of Entropy and Mutual Information

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 ...
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Streaming Pointwise Mutual Information

Streaming Pointwise Mutual Information

wise known as pointwise mutual information (PMI), in a streaming context. ... and Pantel [2004], introduced a probabilistic model for learning Shankian script-like ...by B Van Durme · ‎Cited by 37 · ‎Related articles
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Alignment by Maximization of Mutual Information 1 Introduction

Alignment by Maximization of Mutual Information 1 Introduction

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
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Mutual Information Applied to Anomaly Detection

Mutual Information Applied to Anomaly Detection

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
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1 A Few More Facts about Mutual Information 2 KL Divergence

1 A Few More Facts about Mutual Information 2 KL Divergence

Lecture Notes 7: ... The following claim states that post-processing cannot increase the amount of information ... Lemma 2 (Information Processing Inequality).
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Estimating Mutual Information on Data Streams

Estimating Mutual Information on Data Streams

Jul 1, 2015 — Also note that the problem considered in [14] is entirely different: They investigate pointwise mutual information. (PMI), a formalization of the ...by F Keller · ‎Cited by 15 · ‎Related articles
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Entropy and Mutual Information Chapter 2 outline

Entropy and Mutual Information Chapter 2 outline

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
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Normalized Mutual Information Feature Selection

Normalized Mutual Information Feature Selection

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
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Crisp Boundary Detection Using Pointwise Mutual Information

Crisp Boundary Detection Using Pointwise Mutual Information

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
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Entropy Power, Autoregressive Models, and Mutual Information

Entropy Power, Autoregressive Models, and Mutual Information

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
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Optimal Mutual Information Quantization is NP-complete

Optimal Mutual Information Quantization is NP-complete

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
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Information Model for Non-hierarchical Information Management

Information Model for Non-hierarchical Information Management

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
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Feedback and Side-Information in Information Theory

Feedback and Side-Information in Information Theory

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.
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From Information Retrieval to Information Interaction

From Information Retrieval to Information Interaction

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
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What kind of information is brain information?

What kind of information is brain information?

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 ...
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Information theory and Deep learning - Information Theory Lab

Information theory and Deep learning - Information Theory Lab

✤ Information bottleneck and deep learning. ✤ Relationship hotly disputed. Need strong MI estimators! ✤ Conditional mutual information estimation. ✤ Plays vital ...
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