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- Afonso S. Bandeira, Edgar Dobriban, Dustin G. Mixon, William F. Sawin
- IEEE Transactions on Information Theory
- 2013

This paper is concerned with an important matrix condition in compressed sensing known as the restricted isometry property (RIP). We demonstrate that testing whether a matrix satisfies RIP is… (More)

- Edgar Dobriban
- 2016

Principal component analysis (PCA) is a widely used method for dimension reduction. In high dimensional data, the “signal” eigenvalues corresponding to weak principal components (PCs) do not… (More)

- Edgar Dobriban, Jianqing Fan
- Communications in mathematics and statistics
- 2016

Statistical and machine learning theory has developed several conditions ensuring that popular estimators such as the Lasso or the Dantzig selector perform well in high-dimensional sparse regression,… (More)

Suppose we observe data of the form Yi = Di(Si + εi) ∈ R or Yi = DiSi + εi ∈ R, i = 1, . . . , n, where Di ∈ Rp×p are known diagonal matrices, εi are noise, and we wish to perform principal component… (More)

Many applications involve large datasets with entries from exponential family distributions. Our main motivating application is photon-limited imaging, where we observe images with… (More)

- Edgar Dobriban, Kristen Fortney, Stuart K. Kim, Art B. Owen
- Biometrika
- 2015

We develop a new method for large-scale frequentist multiple testing with Bayesian prior information. We find optimal [Formula: see text]-value weights that maximize the average power of the weighted… (More)

- Kristen Fortney, Edgar Dobriban, +9 authors Hao Li
- PLoS genetics
- 2015

We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related… (More)

- Edgar Dobriban
- Information and inference : a journal of the IMA
- 2018

Researchers in data-rich disciplines-think of computational genomics and observational cosmology-often wish to mine large bodies of [Formula: see text]-values looking for significant effects, while… (More)

- Edgar Dobriban, William Leeb, Amit Singer September
- 2018

We consider the linearly transformed spiked model, where observations Yi are noisy linear transforms of unobserved signals of interest Xi:

- Edgar Dobriban
- 2017

Factor analysis is widely used in many application areas. The first step, choosing the number of factors, remains a serious challenge. One of the most popular methods is parallel analysis (PA), which… (More)

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