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Results: 48
Number of items: 48
  • 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
    Deng, S., Sprangers, O., Li, M., Schelter, S., & de Rijke, M. (2024). Domain Generalization in Time Series Forecasting. ACM Transactions on Knowledge Discovery from Data, 18(5), Article 113. https://doi.org/10.1145/3643035
  • 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
    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
    Sprangers, O., Wadman, W., Schelter, S., & de Rijke, M. (2024). Hierarchical forecasting at scale. International Journal of Forecasting, 40(4), 1689-1700. https://doi.org/10.1016/j.ijforecast.2024.02.006
  • 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
  • Open Access
    Sarvi, F., Vardasbi, A., Aliannejadi, M., Schelter, S., & de Rijke, M. (2023). On the Impact of Outlier Bias on User Clicks. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 18-27). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591745
  • Open Access
    Grafberger, S., Groth, P., & Schelter, S. (2023). Provenance Tracking for End-to-End Machine Learning Pipelines. In The ACM Web Conference 2023: Companion of the World Wide Web Conference WWW 2023 : April 30-May 4, 2023, Austin, Texas, USA (pp. 1512). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587557
  • 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
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