3 citations · 9 across the 10 of their papers we have counts for
3 papers · 1 filter
AutoML in Heavily Constrained Applications
Felix Neutatz, Marius Lindauer, Ziawasch Abedjan
Optimizing a machine learning pipeline for a task at hand requires careful configuration of various hyperparameters, typically supported by an AutoML system that optimizes the hype…
Learning Action Embeddings for Off-Policy Evaluation
Matej Cief, Jacek Golebiowski, Philipp Schmidt +2
Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy. OPE is a viable alternative to run…
ED2: Two-stage Active Learning for Error Detection -- Technical Report
Felix Neutatz, Mohammad Mahdavi, Ziawasch Abedjan
Traditional error detection approaches require user-defined parameters and rules. Thus, the user has to know both the error detection system and the data. However, we can also form…