Knowledge graphs (KGs) are known for their large scale and knowledge
inf...
An important problem in large scale inference is the identification of
v...
When can reliable inference be drawn in the "Big Data" context? This pap...
This paper proposes a general adaptive procedure for budget-limited pred...
Several methods have been recently proposed for estimating sparse Gaussi...
Graphical models have proven to be powerful tools for representing
high-...
Sparse high dimensional graphical model selection is a topic of much int...
We introduce a new approach to variable selection, called Predictive
Cor...
The L1-regularized maximum likelihood estimation problem has recently be...
The graphical lasso (glasso) is a widely-used fast algorithm for estimat...
This paper treats the problem of screening for variables with high
corre...