382 citations · 920 across the 11 of their papers we have counts for
3 papers · 1 filter
Flow-Loss: Learning Cardinality Estimates That Matter
Parimarjan Negi, Ryan Marcus, Andreas Kipf +4
Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make…
Bao: Learning to Steer Query Optimizers
Ryan Marcus, Parimarjan Negi, Hongzi Mao +3
Query optimization remains one of the most challenging problems in data management systems. Recent efforts to apply machine learning techniques to query optimization challenges hav…
Neo: A Learned Query Optimizer
Ryan Marcus, Parimarjan Negi, Hongzi Mao +5
Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex component…