Tamara Broderick

TL;DR: SDA-Bayes as mentioned in this paper is a framework for streaming and distributed computation of a Bayesian posterior, which makes streaming updates to the estimated posterior according to a user-specified approximation batch primitive.

TL;DR: TheMAQC Society Board of Directors*, Levi Waldron, Bo Wang, Chris McIntosh, Anna Goldenberg, Anshul Kundaje, Casey S. Greene, Tamara Broderick, Michael M. Hoffman, Jeffrey T. Leek, Keegan Korthauer, Wolfgang Huber, Joelle Pineau, Robert Tibshirani, Trevor Hastie, John P. Ioannidis, John Quackenbush & Hugo J. W. Aerts

TL;DR: SDA-Bayes is presented, a framework for streaming updates to the estimated posterior of a Bayesian posterior, with variational Bayes (VB) as the primitive, and the usefulness of the framework is demonstrated by fitting the latent Dirichlet allocation model to two large-scale document collections.

TL;DR: In this paper, the authors presented the results of attempts to detect the ellipticity of dark matter halos using galaxy-galaxy weak lensing with SDSS data, using 2,020,256 galaxies brighter than r=19 with photometric redshifts as lenses and 31,697,869 source galaxies.

TL;DR: In this article, the authors present the results of attempts to detect the ellipticity of dark matter haloes using galaxy-galaxy weak lensing with SDSS data. But the results appear to be mildly inconsistent with a previously reported detection by Hoekstra, Yee & Gladders, but more data and further tests are needed to clarify whether the discrepancy is real or a consequence of differences in the lens galaxy samples used and analysis methods.