11 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.AI2020★ 11 cited
Causal Inference in the Presence of Interference in Sponsored Search Advertising
Razieh Nabi, Joel Pfeiffer, Murat Ali Bayir +2
In classical causal inference, inferring cause-effect relations from data relies on the assumption that units are independent and identically distributed. This assumption is violat…
cs.LG2020
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Murat Ali Bayir, Joesph J. Pfeiffer +2
It is often critical for prediction models to be robust to distributional shifts between training and testing data. From a causal perspective, the challenge is to distinguish the s…
cs.LG2018★ 5 cited
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks
John Moore, Joel Pfeiffer, Kai Wei +5
In real world systems, the predictions of deployed Machine Learned models affect the training data available to build subsequent models. This introduces a bias in the training data…