Co-occurring keywords · papers mentioning both
Papers
Learning partial correlation graphs and graphical models by covariance queries
JMLR 2021
High-dimensional Linear Discriminant Analysis Classifier for Spiked Covariance Model
JMLR 2020
Targeted Fused Ridge Estimation of Inverse Covariance Matrices from Multiple High-Dimensional Data Classes
JMLR 2020
SVD-Based Screening for the Graphical Lasso
IJCAI 2017
Joint Structural Estimation of Multiple Graphical Models
JMLR 2016
Learning Latent Variable Gaussian Graphical Models
ICML 2014
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables
NeurIPS 2013
Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods
AISTATS 2013
Learning Gaussian Graphical Models with Observed or Latent FVSs
NeurIPS 2013
On the Sample Complexity of Robust PCA
NeurIPS 2012
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses
NeurIPS 2012
Variable Selection for Gaussian Graphical Models
AISTATS 2012
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation
NeurIPS 2011
Extended Bayesian Information Criteria for Gaussian Graphical Models
NeurIPS 2010