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Results: 48
Number of items: 48
  • Open Access
    Schelter, S., Grafberger, S., & de Rijke, M. (2024). Snarcase - Regain Control over Your Predictions with Low-Latency Machine Unlearning. Proceedings of the VLDB Endowment, 17(12), 4273-4276. https://doi.org/10.14778/3685800.3685853
  • Open Access
    Sprangers, O. R. (2024). Efficient and accurate forecasting in large-scale settings. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kersbergen, B., Sprangers, O., Kootte, F., Guha, S., de Rijke, M., & Schelter, S. (2024). Etude - Evaluating the Inference Latency of Session-Based Recommendation Models at Scale. In 2024 IEEE 40th International Conference on Data Engineering: ICDE 2024 : 13-17 May 2024, Utrecht, Netherlands : proceedings (pp. 5177-5183). IEEE Computer Society. https://doi.org/10.1109/icde60146.2024.00389
  • Open Access
    Döhmen, T., Geacu, R., Hulsebos, M., & Schelter, S. (2024). SchemaPile: A Large Collection of Relational Database Schemas. Proceedings of the ACM on Management of Data, 2(3), Article 172. https://doi.org/10.1145/3654975
  • Open Access
    Zhang, Z., Groth, P., Calixto, I., & Schelter, S. (2024). Directions Towards Efficient and Automated Data Wrangling with Large Language Models. In 2024 IEEE 40th International Conference on Data Engineering Workshops: ICDEW 2024 : 13-17 May 2024, Utrecht, Netherlands : proceedings (pp. 301-304). IEEE Computer Society. https://doi.org/10.1109/ICDEW61823.2024.00044
  • Open Access
    Sarvi, F., Aliannejadi, M., Schelter, S., & de Rijke, M. (2023). How to Make an Outlier? Studying the Effect of Presentational Features on the Outlierness of Items in Product Search Results. In CHIIR'23: proceedings of the 2023 Conference on Human Information Interaction and Retrieval : March 19-23, 2023, Austin, Texas, USA (pp. 346-350). The Association for Computing Machinery. https://doi.org/10.1145/3576840.3578278
  • Open Access
    Sprangers, O., Schelter, S., & de Rijke, M. (2023). Parameter Efficient Deep Probabilistic Forecasting. International Journal of Forecasting, 39(1), 332-345. https://doi.org/10.1016/j.ijforecast.2021.11.011
  • Open Access
    Schelter, S., Grafberger, S., Guha, S., Karlaš, B., & Zhang, C. (2023). Proactively Screening Machine Learning Pipelines with ArgusEyes. In SIGMOD '23 Companion: Companion of the 2023 ACM/SIGMOD International Conference on Management of Data : June 18-23, 2023, Seattle, WA, USA (pp. 91–94). Association for Computing Machinery. https://doi.org/10.1145/3555041.3589682
  • Open Access
    Ariannezhad, M. (2023). User-oriented recommender systems in retail. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Guha, S., Khan, F. A., Stoyanovich, J., & Schelter, S. (2023). Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making. In 2023 IEEE 39th International Conference on Data Engineering: ICDE 2023 : proceedings : 3-7 April 2023, Anaheim, California (pp. 3747-3754). IEEE Computer Society. https://doi.org/10.1109/ICDE55515.2023.00303
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