Stefan Grafberger

25 papers A* 1A 3Journal 13Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Ninth Workshop on Data Management for End-to-End Machine Learning (DEEM). SIGMOD Conference Companion Stefan Grafberger, Madelon Hulsebos, Matteo Interlandi, Shreya Shankar
2025	A	`conf`	Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Platform: Can One QO Rule Them All? CIDR Yuanyuan Tian, Jesús Camacho-Rodríguez, Carlo Curino, César A. Galindo-Legaria, Ashit Gosalia, Brian Kroth, Sergiy Matusevych, Nicolas Bruno, Ashvin Agrawal, Stefan Grafberger, Beysim Sezgin, Milan Potocnik, Mahesh Behera, Milind Joshi, Xiaoyu Li
2025	—	`conf`	Towards Regaining Control Over Messy Machine Learning Pipelines. ICDEW Stefan Grafberger, Hao Chen, Olga Ovcharenko, Sebastian Schelter
2025	J	`jnl`	mlidea: Interactively Improving ML Data Preparation Code via "Shadow Pipelines". Proc. VLDB Endow. Stefan Grafberger, Paul Groth, Sebastian Schelter
2024	J	`jnl`	Automated Provenance-Based Screening of ML Data Preparation Pipelines. Datenbank-Spektrum Sebastian Schelter, Shubha Guha, Stefan Grafberger
2024	J	`jnl`	Instrumentation and Analysis of Native ML Pipelines via Logical Query Plans. CoRR Stefan Grafberger
2024	J	`jnl`	Messy Code Makes Managing ML Pipelines Difficult? Just Let LLMs Rewrite the Code! CoRR Sebastian Schelter, Stefan Grafberger
2024	J	`jnl`	Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. IEEE Data Eng. Bull. Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang
2024	J	`jnl`	Snapcase - Regain Control over Your Predictions with Low-Latency Machine Unlearning. Proc. VLDB Endow. Sebastian Schelter, Stefan Grafberger, Maarten de Rijke
2024	—	`conf`	Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". DEEM@SIGMOD Stefan Grafberger, Paul Groth, Sebastian Schelter
2024	J	`jnl`	Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". CoRR Stefan Grafberger, Paul Groth, Sebastian Schelter
2024	J	`jnl`	Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? CoRR Rana Alotaibi, Yuanyuan Tian, Stefan Grafberger, Jesús Camacho-Rodríguez, Nicolas Bruno, Brian Kroth, Sergiy Matusevych, Ashvin Agrawal, Mahesh Behera, Ashit Gosalia, César A. Galindo-Legaria, Milind Joshi, Milan Potocnik, Beysim Sezgin, Xiaoyu Li, Carlo Curino
2023	J	`jnl`	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines. Proc. ACM Manag. Data Stefan Grafberger, Paul Groth, Sebastian Schelter
2023	J	`jnl`	How to Compliment a Human - Designing Affective and Well-being Promoting Conversational Things. CoRR Ilhan Aslan, Dominik Neu, Daniela Neupert, Stefan Grafberger, Nico Weise, Pascal Pfeil, Maximilian Kuschewski
2023	J	`jnl`	Improving Retrieval-Augmented Large Language Models via Data Importance Learning. CoRR Xiaozhong Lyu, Stefan Grafberger, Samantha Biegel, Shaopeng Wei, Meng Cao, Sebastian Schelter, Ce Zhang
2023	J	`jnl`	MLWHATIF: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over? Proc. VLDB Endow. Stefan Grafberger, Shubha Guha, Paul Groth, Sebastian Schelter
2023	—	`conf`	Proactively Screening Machine Learning Pipelines with ARGUSEYES. SIGMOD Conference Companion Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang
2023	—	`conf`	Provenance Tracking for End-to-End Machine Learning Pipelines. WWW (Companion Volume) Stefan Grafberger, Paul Groth, Sebastian Schelter
2022	J	`jnl`	Data distribution debugging in machine learning pipelines. VLDB J. Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter
2022	A	`conf`	Screening Native Machine Learning Pipelines with ArgusEyes. CIDR Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang
2022	—	`conf`	Towards data-centric what-if analysis for native machine learning pipelines. DEEM@SIGMOD Stefan Grafberger, Paul Groth, Sebastian Schelter
2021	—	`conf`	HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning. SIGMOD Conference Sebastian Schelter, Stefan Grafberger, Ted Dunning
2021	A	`conf`	Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. CIDR Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter
2021	—	`conf`	MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. SIGMOD Conference Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter
2019	A*	`conf`	Differential Data Quality Verification on Partitioned Data. ICDE Sebastian Schelter, Stefan Grafberger, Philipp Schmidt, Tammo Rukat, Mario Kießling, Andrey Taptunov, Felix Bießmann, Dustin Lange