187 citations · 423 across the 18 of their papers we have counts for
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cs.CL2018★ 25 cited
Learning to Segment Inputs for NMT Favors Character-Level Processing
Julia Kreutzer, Artem Sokolov
Most modern neural machine translation (NMT) systems rely on presegmented inputs. Segmentation granularity importantly determines the input and output sequence lengths, hence the m…
stat.ML2018★ 4 cited
Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction
Artem Sokolov, Julian Hitschler, Mayumi Ohta +1
Stochastic zeroth-order (SZO), or gradient-free, optimization allows to optimize arbitrary functions by relying only on function evaluations under parameter perturbations, however,…