Ensemble estimation of generalized mutual information with applications to genomics
Mutual information is a measure of the dependence between random variables that has
been used successfully in myriad applications in many fields. Generalized mutual …
been used successfully in myriad applications in many fields. Generalized mutual …
Ensemble Estimation of Generalized Mutual Information with Applications to Genomics
KR Moon, K Sricharan, AO Hero III - arXiv preprint arXiv:1701.08083, 2017 - arxiv.org
Mutual information is a measure of the dependence between random variables that has
been used successfully in myriad applications in many fields. Generalized mutual …
been used successfully in myriad applications in many fields. Generalized mutual …
Ensemble estimation of mutual information
We derive the mean squared error convergence rates of kernel density-based plug-in
estimators of mutual information measures between two multidimensional random variables …
estimators of mutual information measures between two multidimensional random variables …
Jackknife approach to the estimation of mutual information
Quantifying the dependence between two random variables is a fundamental issue in data
analysis, and thus many measures have been proposed. Recent studies have focused on …
analysis, and thus many measures have been proposed. Recent studies have focused on …
Estimating mutual information by local Gaussian approximation
Estimating mutual information (MI) from samples is a fundamental problem in statistics,
machine learning, and data analysis. Recently it was shown that a popular class of non …
machine learning, and data analysis. Recently it was shown that a popular class of non …
A computationally efficient estimator for mutual information
D Evans - Proceedings of the Royal Society A …, 2008 - royalsocietypublishing.org
Mutual information quantifies the determinism that exists in a relationship between random
variables, and thus plays an important role in exploratory data analysis. We investigate a …
variables, and thus plays an important role in exploratory data analysis. We investigate a …
Exponential concentration for mutual information estimation with application to forests
H Liu, L Wasserman, J Lafferty - Advances in Neural …, 2012 - proceedings.neurips.cc
We prove a new exponential concentration inequality for a plug-in estimator of the Shannon
mutual information. Previous results on mutual information estimation only bounded …
mutual information. Previous results on mutual information estimation only bounded …
Computationally efficient estimation of squared-loss mutual information with multiplicative kernel models
T Sakai, M Sugiyama - IEICE TRANSACTIONS on Information and …, 2014 - search.ieice.org
Squared-loss mutual information (SMI) is a robust measure of the statistical dependence
between random variables. The sample-based SMI approximator called least-squares …
between random variables. The sample-based SMI approximator called least-squares …
Analysis of KNN information estimators for smooth distributions
KSG mutual information estimator, which is based on the distances of each sample to its k-th
nearest neighbor, is widely used to estimate mutual information between two continuous …
nearest neighbor, is widely used to estimate mutual information between two continuous …
[HTML][HTML] Bayesian and quasi-Bayesian estimators for mutual information from discrete data
Mutual information (MI) quantifies the statistical dependency between a pair of random
variables, and plays a central role in the analysis of engineering and biological systems …
variables, and plays a central role in the analysis of engineering and biological systems …