Search Results for author: Michael A. Newton

Found 3 papers, 1 papers with code

Bayes Optimal Informer Sets for Early-Stage Drug Discovery

2 code implementations11 Nov 2020 Peng Yu, Spencer S. Ericksen, Anthony Gitter, Michael A. Newton

An IBR method selects an informer set of compounds, and then prioritizes the remaining compounds on the basis of new bioactivity experiments performed with the informer set on the target.

Methodology

Random weighting in LASSO regression

no code implementations7 Feb 2020 Tun Lee Ng, Michael A. Newton

We establish statistical properties of random-weighting methods in LASSO regression under different regularization parameters $\lambda_n$ and suitable regularity conditions.

Methodology 62F12, 62F40, 62F15

Making the cut: improved ranking and selection for large-scale inference

no code implementations19 Dec 2013 Nicholas C. Henderson, Michael A. Newton

We describe and evaluate a generic empirical Bayesian ranking procedure that populates the list of top units in a way that maximizes the expected overlap between the true and reported top lists for all list sizes.

Methodology

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