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Inferring the Causal Impact of New Track Releases on Music Recommendation Platforms through Counterfactual Predictions., , and . RecSys, page 687-691. ACM, (2020)Contextual and Sequential User Embeddings for Large-Scale Music Recommendation., , , , , , and . RecSys, page 53-62. ACM, (2020)Towards Task Understanding in Visual Settings., , , and . CoRR, (2018)The Multisided Complexity of Fairness in Recommender Systems., , , and . AI Mag., 43 (2): 164-176 (2022)Towards Hierarchies of Search Tasks & Subtasks., and . WWW (Companion Volume), page 73-74. ACM, (2015)Overview of the TREC 2015 Tasks Track., , , , , and . TREC, volume 500-319 of NIST Special Publication, National Institute of Standards and Technology (NIST), (2015)On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat., , , , , , , , , and . FIRE, page 136-141. ACM, (2023)Task-Based User Modelling for Personalization via Probabilistic Matrix Factorization., , and . RecSys Posters, volume 1247 of CEUR Workshop Proceedings, CEUR-WS.org, (2014)Towards a Fair Marketplace: Counterfactual Evaluation of the trade-off between Relevance, Fairness & Satisfaction in Recommendation Systems., , , , and . CIKM, page 2243-2251. ACM, (2018)Inferring User Needs & Tasks from User Interactions.. SIGIR Forum, 52 (2): 176-177 (2018)