9 citations · 10 across the 6 of their papers we have counts for
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cs.LG2019
Toward a Characterization of Loss Functions for Distribution Learning
Nika Haghtalab, Cameron Musco, Bo Waggoner
In this work we study loss functions for learning and evaluating probability distributions over large discrete domains. Unlike classification or regression where a wide variety of…
cs.LG2019★ 9 cited
Learning to Prune: Speeding up Repeated Computations
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett +3
It is common to encounter situations where one must solve a sequence of similar computational problems. Running a standard algorithm with worst-case runtime guarantees on each inst…