8 citations · 11 across the 2 of their papers we have counts for
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stat.ML2019
Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning
Robin Vogel, Aurélien Bellet, Stephan Clémençon +2
The development of cluster computing frameworks has allowed practitioners to scale out various statistical estimation and machine learning algorithms with minimal programming effor…
stat.ML2015★ 3 cited
Survey schemes for stochastic gradient descent with applications to M-estimation
Stéphan Clémençon, Patrice Bertail, Emilie Chautru +1
In certain situations that shall be undoubtedly more and more common in the Big Data era, the datasets available are so massive that computing statistics over the full sample is ha…