Exploring author gender in book rating and recommendation von Ekstrand, Michael D., Kluver, Daniel

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Preface to the special issue on fair, accountable, and transparent recommender systems von Burke, Robin, Ekstrand, Michael D., Tintarev, Nava, Vassileva, Julita

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Enhancing classroom instruction with online news von Ekstrand, Michael D, Wright, Katherine Landau, Pera, Maria Soledad

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Towards Optimizing Ranking in Grid-Layout for Provider-Side Fairness von Raj, Amifa, Ekstrand, Michael D.

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Multiple Testing for IR and Recommendation System Experiments von Ihemelandu, Ngozi, Ekstrand, Michael D.

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Teaching Recommender Systems at Large Scale: Evaluation and Lessons Learned from a Hybrid MOOC von Konstan, Joseph A., Walker, J. D., Brooks, D. Christopher, Brown, Keith, Ekstrand, Michael D.

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Not Just Algorithms: Strategically Addressing Consumer Impacts in Information Retrieval von Ekstrand, Michael D., Beattie, Lex, Pera, Maria Soledad, Cramer, Henriette

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Rating-Based Collaborative Filtering: Algorithms and Evaluation von Kluver, Daniel, Ekstrand, Michael D., Konstan, Joseph A.

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Distributionally-Informed Recommender System Evaluation von Ekstrand, Michael D., Carterette, Ben, Diaz, Fernando

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Candidate Set Sampling for Evaluating Top-N Recommendation von Ihemelandu, Ngozi, Ekstrand, Michael D

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Towards Measuring Fairness in Grid Layout in Recommender Systems von Raj, Amifa, Ekstrand, Michael D

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Inference at Scale Significance Testing for Large Search and Recommendation Experiments von Ihemelandu, Ngozi, Ekstrand, Michael D

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Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation von Ekstrand, Michael D

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It's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation von Ferraro, Andres, Ekstrand, Michael D, Bauer, Christine

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Fire Dragon and Unicorn Princess; Gender Stereotypes and Children's Products in Search Engine Responses von Raj, Amifa, Ekstrand, Michael D

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RecBench: benchmarks for evaluating performance of recommender system architectures von Levandoski, Justin J., Ekstrand, Michael D., Ludwig, Michael J., Eldawy, Ahmed, Mokbel, Mohamed F., Riedl, John T.

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LensKit for Python: Next-Generation Software for Recommender System Experiments von Ekstrand, Michael D

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Distributionally-Informed Recommender System Evaluation von Ekstrand, Michael D, Carterette, Ben, Diaz, Fernando

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Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse von Ihemelandu, Ngozi, Ekstrand, Michael D

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Recall, Robustness, and Lexicographic Evaluation von Diaz, Fernando, Ekstrand, Michael D, Mitra, Bhaskar

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