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Results: 47
Number of items: 47
  • Open Access
    Grafberger, S., Groth, P., & Schelter, S. (2025). mlidea: Interactively Improving ML Data Preparation Code via "Shadow Pipelines". Proceedings of the VLDB Endowment, 18(12), 5359–5362. https://doi.org/10.14778/3750601.3750671
  • Open Access
    Sarvi, F. (2025). Learning to rank for e-commerce search. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Grafberger, S. (2025). Declarative machine learning pipeline management via logical query plans. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kersbergen, B. (2025). Expanding boundaries in scalable session-based recommendations. [Thesis, fully internal, Universiteit van Amsterdam].
  • Döhmen, T., Radu, G., Hulsebos, M., & Schelter, S. (2024, July 7). SchemaPile: A Large Collection of Relational Database Schemas [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12682521
  • Open Access
    Redyuk, S., Kaoudi, Z., Schelter, S., & Markl, V. (2024). Assisted design of data science pipelines. The VLDB Journal, 33(4), 1129-1153. https://doi.org/10.1007/s00778-024-00835-2
  • 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
    Grafberger, S., Groth, P., & Schelter, S. (2024). Towards Interactively Improving ML Data Preparation Code via “Shadow Pipelines”. In Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning (DEEM): in conjunction with the 2024 ACM SIGMOD/PODS Conference, Santiago, Chile (pp. 7–11). The Association for Computing Machinery. https://doi.org/10.1145/3650203.3663327
  • Open Access
    Sprangers, O. R. (2024). Efficient and accurate forecasting in large-scale settings. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
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