5 citations · 5 across the 1 of their papers we have counts for
3 papers
cs.DB2022★ 5 cited
Management of Machine Learning Lifecycle Artifacts: A Survey
Marius Schlegel, Kai-Uwe Sattler
The explorative and iterative nature of developing and operating machine learning (ML) applications leads to a variety of artifacts, such as datasets, features, models, hyperparame…
cs.DB2021
Updatable Materialization of Approximate Constraints
Steffen Kläbe, Kai-Uwe Sattler, Stephan Baumann
Modern big data applications integrate data from various sources. As a result, these datasets may not satisfy perfect constraints, leading to sparse schema information and non-opti…
cs.DB2020
Data Structure Primitives on Persistent Memory: An Evaluation
Philipp Götze, Arun Kumar Tharanatha, Kai-Uwe Sattler
Persistent Memory (PMem), as already available, e.g., with Intel Optane DC Persistent Memory, represents a very promising, next-generation memory solution with a significant impact…