| HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning S Schelter, S Grafberger, T Dunning Proceedings of the 2021 International Conference on Management of Data, 1545 …, 2021 | 95 | 2021 |
| Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines S Grafberger, J Stoyanovich, S Schelter Conference on Innovative Data Systems Research (CIDR), 2021 | 45 | 2021 |
| mlinspect: A Data Distribution Debugger for Machine Learning Pipelines S Grafberger, S Guha, J Stoyanovich, S Schelter Proceedings of the 2021 International Conference on Management of Data, 2736 …, 2021 | 40 | 2021 |
| Data distribution debugging in machine learning pipelines S Grafberger, P Groth, J Stoyanovich, S Schelter The VLDB Journal 31 (5), 1103-1126, 2022 | 30 | 2022 |
| Deequ - Data Quality Validation for Machine Learning Pipelines S Schelter, S Grafberger, P Schmidt, T Rukat, M Kiessling, A Taptunov, ... Machine Learning Systems workshop at the conference on Neural Information …, 2018 | 23 | 2018 |
| Differential Data Quality Verification on Partitioned Data S Schelter, S Grafberger, P Schmidt, T Rukat, M Kiessling, A Taptunov, ... 2019 IEEE 35th International Conference on Data Engineering (ICDE), 1940-1945, 2019 | 22 | 2019 |
| Screening Native ML Pipelines with “ArgusEyes” S Schelter, S Grafberger, S Guha, O Sprangers, B Karlaš, C Zhang Conference on Innovative Data Systems Research. CIDR, 2022 | 15 | 2022 |
| Improving Retrieval-Augmented Large Language Models via Data Importance Learning X Lyu, S Grafberger, S Biegel, S Wei, M Cao, S Schelter, C Zhang arXiv preprint arXiv:2307.03027, 2023 | 13 | 2023 |
| Automating and optimizing data-centric what-if analyses on native machine learning pipelines S Grafberger, P Groth, S Schelter Proceedings of the ACM on Management of Data 1 (2), 1-26, 2023 | 12 | 2023 |
| Proactively screening machine learning pipelines with arguseyes S Schelter, S Grafberger, S Guha, B Karlas, C Zhang Companion of the 2023 International Conference on Management of Data, 91-94, 2023 | 12 | 2023 |
| mlwhatif: What if you could stop re-implementing your machine learning pipeline analyses over and over? S Grafberger, S Guha, P Groth, S Schelter Proceedings of the VLDB Endowment 16 (12), 4002-4005, 2023 | 8 | 2023 |
| Towards Data-Centric What-If Analysis for Native Machine Learning Pipelines S Grafberger, P Groth, S Schelter Proceedings of the Sixth Workshop on Data Management for End-To-End Machine …, 2022 | 7 | 2022 |
| Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. S Grafberger, Z Zhang, S Schelter, C Zhang IEEE Data Eng. Bull. 47 (1), 63-81, 2024 | 3 | 2024 |
| Provenance tracking for end-to-end machine learning pipelines S Grafberger, P Groth, S Schelter Companion Proceedings of the ACM Web Conference 2023, 1512-1512, 2023 | 3 | 2023 |
| Towards Interactively Improving ML Data Preparation Code via" Shadow Pipelines" S Grafberger, P Groth, S Schelter Proceedings of the Eighth Workshop on Data Management for End-to-End Machine …, 2024 | 2 | 2024 |
| How to Compliment a Human - Designing Affective and Well-being Promoting Conversational Things I Aslan, D Neu, D Neupert, S Grafberger, N Weise, P Pfeil, M Kuschewski Interaction Design and Architecture(s) Journal - IxD&A 10.55612/s-5002-058-007, 2023 | 2 | 2023 |
| Towards Declarative Systems for Data-Centric Machine Learning S Grafberger, B Karlaš, P Groth, S Schelter Proceedings of the Data-Centric Machine Learning Research workshop (DMLR) at …, 2023 | 1 | 2023 |
| Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? R Alotaibi, Y Tian, S Grafberger, J Camacho-Rodríguez, N Bruno, B Kroth, ... Conference on Innovative Data Systems Research (CIDR), 2025 | | 2025 |
| Automated Provenance-Based Screening of ML Data Preparation Pipelines S Schelter, S Guha, S Grafberger Datenbank-Spektrum 24 (3), 187-196, 2024 | | 2024 |
| Messy Code Makes Managing ML Pipelines Difficult? Just Let LLMs Rewrite the Code! S Schelter, S Grafberger arXiv preprint arXiv:2409.10081, 2024 | | 2024 |
Sebastian SchelterProfessor at BIFOLD & TU BerlinE-mail megerősítve itt: tu-berlin.de