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18 papers · 1 filter
MAD-Bayes: MAP-based Asymptotic Derivations from Bayes
Tamara Broderick, Brian Kulis, Michael I. Jordan
The classical mixture of Gaussians model is related to K-means via small-variance asymptotics: as the covariances of the Gaussians tend to zero, the negative log-likelihood of the…
Constraining Cosmic Expansion and Gravity with Galaxy Redshift Surveys
Scott F. Daniel, Eric V. Linder
We analyze the science reach of a next generation galaxy redshift survey such as BigBOSS to fit simultaneously for time varying dark energy equation of state and time- and scale-de…
Distributed Non-Stochastic Experts
Varun Kanade, Zhenming Liu, Bozidar Radunovic
We consider the online distributed non-stochastic experts problem, where the distributed system consists of one coordinator node that is connected to sites, and the sites are r…
Power Spectrum Precision for Redshift Space Distortions
Eric V. Linder, Johan Samsing
Redshift space distortions in galaxy clustering offer a promising technique for probing the growth rate of structure and testing dark energy properties and gravity. We consider the…
Addressing Decadal Survey Science through Community Access to Highly Multiplexed Spectroscopy with BigBOSS on the KPNO Mayall Telescope
Caty Pilachowski, Carles Badenes, Stephen Bailey +87
This document summarizes the results of a community-based discussion of the potential science impact of the Mayall+BigBOSS highly multiplexed multi-object spectroscopic capability.…
Design principles and fundamental trade-offs in biomimetic light harvesting
Mohan Sarovar, K. Birgitta Whaley
Recent developments in synthetic and supramolecular chemistry have created opportunities to design organic systems with tailored nanoscale structure for various technological appli…