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- Peter J Bickel, Alexandre B Ya 'acov Ritov, Tsybakov
- 2008

We exhibit an approximate equivalence between the Lasso es-timator and Dantzig selector. For both methods we derive parallel oracle inequalities for the prediction risk in the general nonparamet-ric regression model, as well as bounds on the ℓp estimation loss for 1 ≤ p ≤ 2 in the linear model when the number of variables can be much larger than the sample… (More)

- Peter J. Bickel
- SIAM Review
- 1994

This paper considers estimating a covariance matrix of p variables from n observations by either banding or tapering the sample covariance matrix, or estimating a banded version of the inverse of the covariance. We show that these estimates are consistent in the operator norm as long as (log p)/n → 0, and obtain explicit rates. The results are uniform over… (More)

The paper proposes a method for constructing a sparse estima-tor for the inverse covariance (concentration) matrix in high-dimensional settings. The estimator uses a penalized normal likelihood approach and forces sparsity by using a lasso-type penalty. We establish a rate of convergence in the Frobenius norm as both data dimension p and sample size n are… (More)

- Elizaveta Levina, Peter J. Bickel
- NIPS
- 2004

We propose a new method for estimating intrinsic dimension of a dataset derived by applying the principle of maximum likelihood to the distances between close neighbors. We derive the estimator by a Poisson process approximation, assess its bias and variance theoretically and by simulations, and apply it to a number of simulated and real datasets. We also… (More)

- Peter J Bickel, Aiyou Chen
- Proceedings of the National Academy of Sciences…
- 2009

Prompted by the increasing interest in networks in many fields, we present an attempt at unifying points of view and analyses of these objects coming from the social sciences, statistics, probability and physics communities. We apply our approach to the Newman-Girvan modularity, widely used for "community" detection, among others. Our analysis is asymptotic… (More)

Reproducibility is essential to reliable scientific discovery in high-throughput experiments. In this work, we propose a unified approach to measure the reproducibility of findings identified from replicate experiments and identify putative discoveries using reproducibility. Unlike the usual scalar measures of reproducibility, our approach creates a curve,… (More)

- Stewart MacArthur, Xiao-Yong Li, +12 authors Michael B Eisen
- Genome Biology
- 2009

We previously established that six sequence-specific transcription factors that initiate anterior/posterior patterning in Drosophila bind to overlapping sets of thousands of genomic regions in blastoderm embryos. While regions bound at high levels include known and probable functional targets, more poorly bound regions are preferentially associated with… (More)

- James B. Brown, Nathan Boley, +38 authors Susan E. Celniker
- Nature
- 2014

Animal transcriptomes are dynamic, with each cell type, tissue and organ system expressing an ensemble of transcript isoforms that give rise to substantial diversity. Here we have identified new genes, transcripts and proteins using poly(A)+ RNA sequencing from Drosophila melanogaster in cultured cell lines, dissected organ systems and under environmental… (More)

- Elizaveta Levina, Peter J. Bickel
- ICCV
- 2001

The Earth Mover's distance was first introduced as a purely empirical way to measure texture and color similarities. We show that it has a rigorous probabilistic interpretation and is conceptually equivalent to the Mallows distance on probability distributions. The two distances are exactly the same when applied to probability distributions, but behave… (More)