9 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.DB2025★ 9 cited
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks
Roman Heinrich, Manisha Luthra, Johannes Wehrstein +2
Traditionally, query optimizers rely on cost models to choose the best execution plan from several candidates, making precise cost estimates critical for efficient query execution.…
cs.DB2022
DiffML: End-to-end Differentiable ML Pipelines
Benjamin Hilprecht, Christian Hammacher, Eduardo Reis +2
In this paper, we present our vision of differentiable ML pipelines called DiffML to automate the construction of ML pipelines in an end-to-end fashion. The idea is that DiffML all…