10 citations · 31 across the 12 of their papers we have counts for
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stat.ML2022
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions
Adam Block, Max Simchowitz
Due to the drastic gap in complexity between sequential and batch statistical learning, recent work has studied a smoothed sequential learning setting, where Nature is constrained…
stat.ML2022★ 2 cited
Smoothed Online Learning is as Easy as Statistical Learning
Adam Block, Yuval Dagan, Noah Golowich +1
Much of modern learning theory has been split between two regimes: the classical offline setting, where data arrive independently, and the online setting, where data arrive adversa…