Co-occurring keywords · papers mentioning both
Papers
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series
AISTATS 2013
Random Design Analysis of Ridge Regression
COLT 2012
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses
NeurIPS 2012
Group Lasso Estimation of High-dimensional Covariance Matrices
JMLR 2011
High-dimensional Covariance Estimation Based On Gaussian Graphical Models
JMLR 2011
Exploiting Feature Covariance in High-Dimensional Online Learning
AISTATS 2010
Tight Sample Complexity of Large-Margin Learning
NeurIPS 2010
The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models
JMLR 2009
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
NeurIPS 2007
Differential Entropic Clustering of Multivariate Gaussians
NeurIPS 2006
Blind Source Separation via Generalized Eigenvalue Decomposition
JMLR 2003