Neural estimation of statistical divergences
S Sreekumar, Z Goldfeld - Journal of machine learning research, 2022 - jmlr.org
Statistical divergences (SDs), which quantify the dissimilarity between probability
distributions, are a basic constituent of statistical inference and machine learning. A modern …
distributions, are a basic constituent of statistical inference and machine learning. A modern …
Ensemble estimation of information divergence
Recent work has focused on the problem of nonparametric estimation of information
divergence functionals between two continuous random variables. Many existing …
divergence functionals between two continuous random variables. Many existing …
Nearest neighbor density functional estimation from inverse Laplace transform
A new approach to-consistent estimation of a general density functional using-nearest
neighbor distances is proposed, where the functional under consideration is in the form of …
neighbor distances is proposed, where the functional under consideration is in the form of …
[PDF][PDF] Estimating probability distributions and their properties
S Singh - 2019 - reports-archive.adm.cs.cmu.edu
This thesis studies several theoretical problems in nonparametric statistics and machine
learning, mostly in the areas of nonparametric density functional estimation (estimating an …
learning, mostly in the areas of nonparametric density functional estimation (estimating an …
Ensemble Estimation of Distributional Functionals via -Nearest Neighbors
The problem of accurate nonparametric estimation of distributional functionals (integral
functionals of one or more probability distributions) has received recent interest due to their …
functionals of one or more probability distributions) has received recent interest due to their …
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 …
Minimax estimation of quadratic Fourier functionals
We study estimation of (semi-) inner products between two nonparametric probability
distributions, given IID samples from each distribution. These products include relatively well …
distributions, given IID samples from each distribution. These products include relatively well …
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 …