Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization
Summary: Frames ML lifecycle management as data management for statistical generalization. ease.ml/ci continuously validates model changes, while ease.ml/meter profiles validation/test sets to control overfitting and preserve reliable quality estimates. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Cedric Renggli (ETH Zurich)
- 2. Frances Ann Hubis (ETH Zurich)
- 3. Bojan Karlas (ETH Zurich)
- 4. Kevin Schawinski (Modulos AG)
- 5. Wentao Wu (Microsoft)
- 6. Ce Zhang (ETH Zurich)
BibTeX Citation
@article{renggli_vldb19,
title = {{Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization}},
author = {Renggli, Cedric and Hubis, Frances Ann and Karlas, Bojan and Schawinski, Kevin and Wu, Wentao and Zhang, Ce},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {1962--1965},
doi = {10.14778/3352063.3352110},
url = {https://doi.org/10.14778/3352063.3352110},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,067 | Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches | 2021 | VLDB | 6.9293511e-05 |
| 4,621 | spade: Synthesizing Data Quality Assertions for Large Language Model Pipelines | 2024 | VLDB | 6.6024412e-05 |
| 11,629 | Ease.ML: A Lifecycle Management System for MLDev and MLOps | 2021 | CIDR | 5.093636e-05 |
| 11,802 | Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development | 2020 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,392 | Northstar: An Interactive Data Science System | 2018 | VLDB | 0.00010936065 |
| 2,029 | Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads | 2018 | VLDB | 9.2843642e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 2,029 | Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads | 2018 | VLDB |
| 2 | 5,297 | An Integrated Development Environment for Faster Feature Engineering | 2014 | VLDB |
| 3 | 7,473 | The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development | 2020 | SIGMOD |
| 4 | 9,265 | Ease.ml in Action: Towards Multi-tenant Declarative Learning Services | 2018 | VLDB |
| 5 | 6,315 | Data Collection and Quality Challenges for Deep Learning | 2020 | VLDB |
| 6 | 11,802 | Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development | 2020 | VLDB |
| 7 | 4,592 | Data Platform for Machine Learning | 2019 | SIGMOD |
| 8 | 11,512 | Towards Observability for Machine Learning Pipelines | 2022 | CIDR |
| 9 | 9,245 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB |
| 10 | 11,629 | Ease.ML: A Lifecycle Management System for MLDev and MLOps | 2021 | CIDR |