Pradeep Ravikumar

most citedHigh-Dimensional Graphical Model Selection Using

ℓ_{1}

-Regularized Logistic Regression

62 citations · 118 across the 3 of their papers we have counts for

collaborators

3 papers

stat.ML2008★ 49 cited

High-dimensional covariance estimation by minimizing $ℓ_{1}$ -penalized log-determinant divergence

Pradeep Ravikumar, Martin J. Wainwright, Garvesh Raskutti +1

Given i.i.d. observations of a random vector $X \in R^{p}$ , we study the problem of estimating both its covariance matrix $Σ^{*}$ , and its inverse covariance or concentration…

math.ST2008★ 62 cited

High-Dimensional Graphical Model Selection Using $ℓ_{1}$ -Regularized Logistic Regression

Pradeep Ravikumar, Martin J. Wainwright, John D. Lafferty

We consider the problem of estimating the graph structure associated with a discrete Markov random field. We describe a method based on $ℓ_{1}$ -regularized logistic regression, in…

math.ST2007★ 7 cited

Sparse Additive Models

Pradeep Ravikumar, John Lafferty, Han Liu +1

We present a new class of methods for high-dimensional nonparametric regression and classification called sparse additive models (SpAM). Our methods combine ideas from sparse linea…

High-dimensional covariance estimation by minimizing ℓ1​-penalized log-determinant divergence

High-Dimensional Graphical Model Selection Using ℓ1​-Regularized Logistic Regression

Sparse Additive Models

High-dimensional covariance estimation by minimizing $ℓ_{1}$ -penalized log-determinant divergence

High-Dimensional Graphical Model Selection Using $ℓ_{1}$ -Regularized Logistic Regression