Publications
Conferences
A. Agarwal, I. Zaitsev, T. Joachims. A General Framework for Counterfactual Learning-to-Rank. SIGIR 2019. (Link)Z. Fang, A. Agarwal, T. Joachims. Intervention Harvesting for Context-Dependent Examination-Bias Estimation. SIGIR 2019. (Link, Code)
A. Agarwal, X. Wang, C. Li, M. Bendersky, M. Najork. Addressing Trust Bias for Unbiased Learning-to-Rank. WWW 2019.(Link)
A. Agarwal, I. Zaitsev, X. Wang, C. Li, M. Najork, T. Joachims. Estimating Position Bias without Intrusive Interventions. WSDM 2019. (Link)
A. Agarwal, S. Basu, T. Schnabel, T. Joachims. Effective Evaluation using Logged Bandit Feedback from Multiple Loggers. KDD 2017. (Link)
Workshops
Z. Fang, A. Agarwal, T. Joachims. Intervention Harvesting for Context-Dependent Examination-Bias Estimation. NeurIPS 2018 Causal Learning Workshop. (Link)A. Agarwal, X. Wang, C. Li, M. Bendersky, M. Najork. Comparison of Ranking Functions using Randomized Data. RecSys 2018 REVEAL Workshop. (Link)
A. Agarwal, I. Zaitsev, T. Joachims. Consistent Position Bias Estimation without Online Interventions for Learning-to-Rank. ICML 2018 CausalML Workshop. (Link)
A. Agarwal, I. Zaitsev, T. Joachims. Counterfactual Learning-to-Rank for Additive Metrics and Deep Models. ICML 2018 CausalML Workshop. (Full version above)
Y. Su, A. Agarwal, T. Joachims. Learning from Logged Bandit Feedback of Multiple Loggers. ICML 2018 CausalML Workshop. (Link)
A. Agarwal, I. Zaitsev, T. Joachims. Counterfactual Learning-to-Rank for Optimizing DCG. WSDM 2018 Task IR Workshop. (Full version above)