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Everything about Conditional mutual information
Information theory
In probability theory, particularly information theory, the conditional mutual information is, in its most basic form, the expected value of the mutual information of two random variables given the value of a third. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Conditional mutual informationA 5-minute orientation
- Skim a recent paper: High-order conditional mutual information maximization for dealing with high-order dependencies in feature selectionInfluential work since 2022
- Pick up a classic book: Poverty and the third wayThe most-reprinted book on the subject
- Read the landmark paper: Quantum Conditional Mutual Information and Approximate Markov ChainsCited 216 times
- Go sideways: Total correlationA closely related topic
- Go sideways: Mutual informationA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Quantum Conditional Mutual Information and Approximate Markov Chains
Nonrigid Image Registration Using Conditional Mutual Information
Inferring the directionality of coupling with conditional mutual information
A definition of conditional mutual information for arbitrary ensembles
Reliability of Inference of Directed Climate Networks Using Conditional Mutual Information
Estimating coupling direction between neuronal populations with permutation conditional mutual information
Mutual Information and Conditional Mean Estimation in Poisson Channels
Conditional Mutual Information-Based Feature Selection Analyzing for Synergy and Redundancy
🆕 Influential since 2022
High-order conditional mutual information maximization for dealing with high-order dependencies in feature selection
A novel information changing rate and conditional mutual information-based input feature selection method for artificial intelligence drought prediction models
Multi-dimensional conditional mutual information with application on the EEG signal analysis for spatial cognitive ability evaluation
A novel method to information fusion in multi-source incomplete interval-valued data via conditional information entropy: Application to mutual information entropy based attribute reduction
Individually Conditional Individual Mutual Information Bound on Generalization Error
📚 Books worth reading
Poverty and the third wayColin C. Williams · 2003
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Total correlation In probability theory and in particular in information theory, total correlation (Watanabe 1960) is one of several generalizations of the mutual information…
- Mutual information In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two…
- Differential entropy Differential entropy (also referred to as continuous entropy) in information theory is a property of absolutely continuous probability distributions which…
- Inequalities in information theory Inequalities are very important in the study of information theory. There are a number of different contexts in which these inequalities appear. Consider…
- Information theory and measure theory This article discusses how information theory (a branch of mathematics studying the transmission, processing and storage of information) is related to…
- Independence (probability theory) Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically…
- Kullback–Leibler divergence In mathematical statistics, the Kullback–Leibler (KL) divergence (also called relative entropy and I-divergence), denoted DKL(P∥Q), is a type of statistical…
- Joint entropy In information theory, joint entropy is a measure of the uncertainty associated with a set of variables. The joint Shannon entropy (in bits) of two discrete…