High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models
From MaRDI portal
Publication:2934033
zbMath1319.62112arXiv1211.0919MaRDI QIDQ2934033
Animashree Anandkumar, Majid Janzamin
Publication date: 8 December 2014
Full work available at URL: https://arxiv.org/abs/1211.0919
convex optimizationcovariance estimationsparsistencysparse covariance modelssparse graphical model selection
Related Items (8)
Tensor clustering with planted structures: statistical optimality and computational limits ⋮ Inference for low-rank tensors -- no need to debias ⋮ Overcomplete Order-3 Tensor Decomposition, Blind Deconvolution, and Gaussian Mixture Models ⋮ Covariate-Assisted Sparse Tensor Completion ⋮ A geometric analysis of phase retrieval ⋮ Comparison of Accuracy and Scalability of Gauss--Newton and Alternating Least Squares for CANDECOMC/PARAFAC Decomposition ⋮ Unnamed Item ⋮ Robust and resource-efficient identification of two hidden layer neural networks
This page was built for publication: High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models