160 citations · 618 across the 56 of their papers we have counts for
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Decentralized optimization with non-identical sampling in presence of stragglers
Tharindu Adikari, Stark Draper
We consider decentralized consensus optimization when workers sample data from non-identical distributions and perform variable amounts of work due to slow nodes known as straggler…
Compressing gradients by exploiting temporal correlation in momentum-SGD
Tharindu B. Adikari, Stark C. Draper
An increasing bottleneck in decentralized optimization is communication. Bigger models and growing datasets mean that decentralization of computation is important and that the amou…
Uncertainty-Aware Learning for Improvements in Image Quality of the Canada-France-Hawaii Telescope
Sankalp Gilda, Stark C. Draper, Sebastien Fabbro +6
We leverage state-of-the-art machine learning methods and a decade's worth of archival data from CFHT to predict observatory image quality (IQ) from environmental conditions and ob…
Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper
We study the problem of community recovery from coarse measurements of a graph. In contrast to the problem of community recovery of a fully observed graph, one often encounters sit…