• Publications
  • Influence
SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR
We show that, under a sparsity scenario, the Lasso estimator and the Dantzig selector exhibit similar behavior. For both methods, we derive, in parallel, oracle inequalities for the prediction risk
Covariance regularization by thresholding
This paper considers regularizing a covariance matrix of $p$ variables estimated from $n$ observations, by hard thresholding. We show that the thresholded estimate is consistent in the operator norm
Efficient and Adaptive Estimation for Semiparametric Models
Introduction.- Asymptotic Inference for (Finite-Dimensional) Parametric Models.- Information Bounds for Euclidean Parameters in Infinite-Dimensional Models.- Euclidean Parameters: Further Examples.-
Regularized estimation of large covariance matrices
TLDR
If the population covariance is embeddable in that model and well-conditioned then the banded approximations produce consistent estimates of the eigenvalues and associated eigenvectors of the covariance matrix.
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.
TLDR
This work discusses how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data and develops a set of working standards and guidelines for ChIP experiments that are updated routinely.
Sparse permutation invariant covariance estimation
TLDR
A method for constructing a sparse estimator for the inverse covariance (concentration) matrix in high-dimensional settings using a penalized normal likelihood approach and forces sparsity by using a lasso-type penalty is proposed.
A nonparametric view of network models and Newman–Girvan and other modularities
  • P. Bickel, Aiyou Chen
  • Computer Science
    Proceedings of the National Academy of Sciences
  • 15 December 2009
TLDR
An attempt at unifying points of view and analyses of these objects coming from the social sciences, statistics, probability and physics communities are presented and the approach to the Newman–Girvan modularity, widely used for “community” detection, is applied.
Some theory for Fisher''s linear discriminant function
Introducing small amounts of cobalt, nickel, or iron into a weld joint between members of aluminum and its alloys substantially eliminates weld porosity. These additives may be included in the rod or
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