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CONSEQUENCES - The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems.

, , , , , and . RecSys, page 1223-1226. ACM, (2023)

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Offline approaches to recommendation with online success. University of Antwerp, Belgium, (2021)Abstract: A Common Misassumption in Online Experiments with Machine Learning Models.. Perspectives@RecSys, volume 3476 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)Closed-Form Models for Collaborative Filtering with Side-Information., , and . RecSys, page 651-656. ACM, (2020)On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat., , , , , , , , , and . FIRE, page 136-141. ACM, (2023)Off-Policy Learning-to-Bid with AuctionGym., , and . KDD, page 4219-4228. ACM, (2023)Learning Metrics that Maximise Power for Accelerated A/B-Tests., and . CoRR, (2024)CONSEQUENCES - The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems., , , , , and . RecSys, page 1223-1226. ACM, (2023)CONSEQUENCES - Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems., , , , and . RecSys, page 654-657. ACM, (2022)Variance Reduction in Ratio Metrics for Efficient Online Experiments., , , and . ECIR (5), volume 14612 of Lecture Notes in Computer Science, page 292-297. Springer, (2024)On (Normalised) Discounted Cumulative Gain as an Offline Evaluation Metric for Top-n Recommendation., , and . CoRR, (2023)