15 citations · 57 across the 29 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★ 1 cited
A General Family of Robust Stochastic Operators for Reinforcement Learning
Yingdong Lu, Mark S. Squillante, Chai Wah Wu
We consider a new family of operators for reinforcement learning with the goal of alleviating the negative effects and becoming more robust to approximation or estimation errors. V…