Voor de beste ervaring schakelt u JavaScript in en gebruikt u een moderne browser!
Je gebruikt een niet-ondersteunde browser. Deze site kan er anders uitzien dan je verwacht.

Dr. ing. S. (Sebastian) Schelter

Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute

Bezoekadres
  • Science Park 904
Postadres
  • Postbus 94323
    1090 GH Amsterdam
  • Publicaties

    2022

    • Sarvi, F., Heuss, M., Aliannejadi, M., Schelter, S., & de Rijke, M. (2022). Understanding and Mitigating the Effect of Outliers in Fair Ranking. In WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining : February 21-25, 2022 : virtual event, Tempe, AZ, USA (pp. 861-869). Association for Computing Machinery. https://doi.org/10.1145/3488560.3498441 [details]

    2021

    • Ariannezhad, M., Jullien, S., Nauts, P., Fang, M., Schelter, S., & de Rijke, M. (2021). Understanding Multi-Channel Customer Behavior in Retail. In CIKM '21: proceedings of the 30th ACM International Conference on Information & Knowledge Management : November 1-5, 2021, virtual event, Australia (pp. 2867–2871). The Association for Computing Machinery. https://doi.org/10.1145/3459637.3482208 [details]
    • Grafberger, S., Guha, S., Stoyanovich, J., & Schelter, S. (2021). MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. In SIGMOD '21: proceedings of the 2021 International Conference on the Management of Data : June 20 -25, 2021, virtual event, China (pp. 2736–2739). Association for Computing Machinery. https://doi.org/10.1145/3448016.3452759 [details]
    • Kersbergen, B., & Schelter, S. (2021). Learnings from a Retail Recommendation System on Billions of Interactions at bol.com. In 2021 IEEE 37th International Conference on Data Engineering: ICDE 2021 : proceedings : Chania, Greece, 19-22 April 2021 (pp. 2447-2452). (International Conference on Data Engineering; Vol. 37). IEEE Computer Society. https://doi.org/10.1109/ICDE51399.2021.00277 [details]
    • Schelter, S. (2021). Letter from the Special Issue Editor. Bulletin of the Technical Committee on Data Engineering, 44(1). http://sites.computer.org/debull/A21mar/issue1.htm
    • Schelter, S., Grafberger, S., & Dunning, T. (2021). HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning. In SIGMOD '21: proceedings of the 2021 International Conference on the Management of Data : June 20 -25, 2021, virtual event, China (pp. 1545–1557). Association for Computing Machinery. https://doi.org/10.1145/3448016.3457239 [details]
    • Sprangers, O., Schelter, S., & de Rijke, M. (2021). Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. In KDD ’21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining : August 14-18, 2021, virtual event, Singapore (pp. 1510-1520). Association for Computing Machinery. https://doi.org/10.1145/3447548.3467278 [details]

    2020

    2021

    • Doehmen, T., Mühleisen, H. F., Raasveldt, M., & Schelter, S. (2021). Data Quality Assertions for Machine Learning Pipeline. Paper presented at Workshop on Challenges in Deploying and Monitoring ML Systems at ICML.
    • Grafberger, S., Stoyanovich, J., & Schelter, S. (2021). Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. Paper presented at Conference on Innovative Data Systems Research (CIDR) 2020, .
    • Grafberger, S., Stoyanovich, J., & Schelter, S. (2021). Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. Paper presented at Conference on Innovative Data Systems Research. http://cidrdb.org/cidr2021/papers/cidr2021_paper27.pdf
    • Redyuk, S., Kaoudi, Z., Markl, V., & Schelter, S. (2021). Automating Data Quality Validation for Dynamic Data Ingestion. Paper presented at International Conference on Extending Database Technology (EDBT 2021).
    • Schelter, S. (2021). Towards Efficient Machine Unlearning via Incremental View Maintenance. Paper presented at Workshop on Challenges in Deploying and Monitoring ML Systems at ICML. https://ssc.io/pdf/ivm-unlearning.pdf
    • Schelter, S., Rukat, T., & Biessmann, F. (2021). Jenga - A Framework to Study the Impact of Data Errors on the Predictions of Machine Learning Models. Paper presented at International Conference on Extending Database Technology (EDBT 2021).
    • Wang, L., & Schelter, S. (2021). Efficiently Maintaining Next Basket Recommendations under Additions and Deletions of Baskets and Items. Paper presented at Workshop on Online Recommender Systems and User Modeling at ACM RecSys. https://orsum.inesctec.pt/orsum2021/assets/files/paper1.pdf
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
  • Nevenwerkzaamheden
    • Ahold Delhaize
      Research Fellow (Director of Engineering and Forecasting)