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In academic literature, recommender systems are often evaluated on the task of next-item prediction.
Some aspects of the sequential design of experiments
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SLIM: Sparse Linear Methods for Top-N Recommender Systems. In Proc. of the 2011 IEEE 11th International Conference on Data Mining
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A Comparative Analysis of Offline and Online Evaluations and Discussion of Research Paper Recommender System Evaluation. In Proc. of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation
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Counterfactual reasoning and learning systems: The example of computational advertising
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Offline and Online Evaluation of News Recommender Systems at Swissinfo.Ch. In Proc. of the 8th ACM Conference on Recommender Systems
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Fair Offline Evaluation Methodologies for Implicit-feedback Recommender Systems with MNAR Data. In Proc. of the REVEAL 18 Workshop on Offline Evaluation for Recommender Systems (RecSys ’18)
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Counterfactual Risk Minimization: Learning from Logged Bandit Feedback. In Proc. of the 32Nd International Conference on International Conference on Machine Learning - Volume 37
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An Improved Multileaving Algorithm for Online Ranker Evaluation. In Proc. of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Local Item-Item Models For Top-N Recommendation. In Proc. of the 10th ACM Conference on Recommender Systems
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Contrasting Offline and Online Results when Evaluating Recommendation Algorithms. In Proc. of the 10th ACM Conference on Recommender Systems
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Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers. In Proc. of the 23rd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
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Translation-based Recommendation. In Proc. of the 11th ACM Conference on Recommender Systems
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Deep Learning with Logged Bandit Feedback. In Proc. of the 6th International Conference on Learning Representations
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Streamingrec: A Framework for Benchmarking Stream-based News Recommenders. In Proc. of the 12th ACM Conference on Recommender Systems
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RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
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HOP-rec: High-order Proximity for Implicit Recommendation. In Proc. of the 12th ACM Conference on Recommender Systems
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Top-K Off-Policy Correction for a REINFORCE Recommender System. In Proc. of the 12th ACM International Conference on Web Search and Data Mining
M. Chen, A. Beutel, P. Covington, S. Jain, F. Belletti, and E. H. Chi. 2019 · 2019
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Offline Evaluation to Make Decisions About Playlist Recommendation Algorithms. In Proceedings of the 12th ACM International Conference on Web Search and Data Mining
A. Gruson, P. Chandar, C. Charbuillet, J. McInerney, S. Hansen, D. Tardieu, and B. Carterette. 2019 · 2019
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When People Change Their Mind: Off-Policy Evaluation in Non-stationary Recommendation Environments. In Proc. of the 12th ACM International Conference on Web Search and Data Mining
R. Jagerman, I. Markov, and M. de Rijke. 2019 · 2019
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Revisiting Offline Evaluation for Implicit-Feedback Recommender Systems. In Proc. of the 13th ACM Conference on Recommender Systems
O. Jeunen. 2019 · 2019
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