27 citations · 50 across the 13 of their papers we have counts for
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stat.ML2018★ 5 cited
Efficient Stochastic Gradient Descent for Learning with Distributionally Robust Optimization
Soumyadip Ghosh, Mark Squillante, Ebisa Wollega
Distributionally robust optimization (DRO) problems are increasingly seen as a viable method to train machine learning models for improved model generalization. These min-max formu…
stat.ML2018★ 27 cited
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh +2
Distributed Stochastic Gradient Descent (SGD) when run in a synchronous manner, suffers from delays in waiting for the slowest learners (stragglers). Asynchronous methods can allev…