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March 7, 2019
Title: A journey to causal advertising: interventions, Datasets & Models
Abstract: In a culture where claims are backed with data, digital advertising shall demonstrate and optimize its causal effect. We will present two use cases from this industry leading to interesting problems. Then we'll describe how to generate datasets to allow for proper counterfactual learning, along with practical optimization tricks and experimental results. Presentation will include material from work published at NeurIPS Causal Learning 2018 and open datasets from Criteo.
Bâtiment IMAG (442)
