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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
    Kersbergen, B. (2025). Expanding boundaries in scalable session-based recommendations. [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].
  • 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
    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
    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
    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
    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
    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
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