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Estimating networks with jumps (Q1950892)

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scientific article

Language	Label	Description	Also known as
English	Estimating networks with jumps	scientific article

Statements

scholarly article

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Estimating networks with jumps (English)

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Electronic Journal of Statistics

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publication date

28 May 2013

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full work available at URL

https://arxiv.org/abs/1012.3795

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https://projecteuclid.org/euclid.ejs/1351865118

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zbMATH Keywords

Gaussian graphical models

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network models

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dynamic network models

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structural changes

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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Estimating and Testing Linear Models with Multiple Structural Changes

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A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

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Regularized estimation of large covariance matrices

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An O(n) algorithm for quadratic knapsack problems

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Honest variable selection in linear and logistic regression models via \(\ell _{1}\) and \(\ell _{1}+\ell _{2}\) penalization

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Network exploration via the adaptive LASSO and SCAD penalties

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Sparse inverse covariance estimation with the graphical lasso

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Pairwise Variable Selection for High-Dimensional Model-Based Clustering

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Joint estimation of multiple graphical models

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Multiple Change-Point Estimation With a Total Variation Penalty

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Estimating time-varying networks

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Gradient directed regularization for sparse Gaussian concentration graphs, with applications to inference of genetic networks

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Locally adaptive regression splines

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High-dimensional graphs and variable selection with the Lasso

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Smooth minimization of non-smooth functions

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Partial Correlation Estimation by Joint Sparse Regression Models

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High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence

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High-dimensional Ising model selection using \(\ell _{1}\)-regularized logistic regression

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Properties and refinements of the fused Lasso

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Sparse permutation invariant covariance estimation

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Sparsity and Smoothness Via the Fused Lasso

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On the conditions used to prove oracle results for the Lasso

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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)

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Graphical Models, Exponential Families, and Variational Inference

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Learning Oncogenic Pathways from Binary Genomic Instability Data

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Model selection and estimation in the Gaussian graphical model

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Identifiers

zbMATH Open document ID

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10.1214/12-EJS739

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:1950892

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