11 citations · 19 across the 6 of their papers we have counts for
7 papers
Impression Share Prediction: An Offline Evaluation Task for Ranking Systems
Mohsen Malmir, Houssam Nassif, Danish Nasir Shaikh +2
Offline evaluation is a major gateway before online evaluation of ranking models in A/B testing. Standard offline metrics measure predictive accuracy, but are only a surrogate for…
Counterfactual Evaluation of Ads Ranking Models through Domain Adaptation
Mohamed A. Radwan, Himaghna Bhattacharjee, Quinn Lanners +4
We propose a domain-adapted reward model that works alongside an Offline A/B testing system for evaluating ranking models. This approach effectively measures reward for ranking mod…
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…
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…
Genie: An Open Box Counterfactual Policy Estimator for Optimizing Sponsored Search Marketplace
Murat Ali Bayir, Mingsen Xu, Yaojia Zhu +1
In this paper, we propose an offline counterfactual policy estimation framework called Genie to optimize Sponsored Search Marketplace. Genie employs an open box simulation engine w…
Link Based Session Reconstruction: Finding All Maximal Paths
Murat Ali Bayir, Ismail Hakki Toroslu
This paper introduces a new method for the session construction problem, which is the first main step of the web usage mining process. Through experiments, it is shown that when ou…
Discovering More Accurate Frequent Web Usage Patterns
Murat Ali Bayir, Ismail Hakki Toroslu, Ahmet Cosar +1
Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web users. As in classical d…