@inproceedings{aguilar2021ease,
author = {Aguilar, Leonel and Dao, David and Gan, Shaoduo and Gurel, Nezihe Merve and Hollenstein, Nora and Jiang, Jiawei and Karlas, Bojan and Lemmin, Thomas and Li, Tian and Li, Yang and Rao, Susie and Rausch, Johannes and Renggli, Cedric and Rimanic, Luka and Weber, Maurice and Zhang, Shuai and Zhao, Zhikuan and Schawinski, Kevin and Wu, Wentao and Zhang, Ce},
title = {Ease.ML: A Lifecycle Management System for MLDev and MLOps},
booktitle = {Conference on Innovative Data Systems Research (CIDR 2021)},
year = {2021},
month = {January},
abstract = {We present Ease.ML, a lifecycle management system for machine learning (ML). Unlike many existing works, which focus on improving individual steps during the lifecycle of ML application development, Ease.ML focuses on managing and automating the entire lifecycle itself. We present user scenarios that have motivated the development of Ease.ML, the eight-step Ease.ML process that covers the lifecycle of ML application development; the foundation of Ease.ML in terms of a probabilistic database model and its connection to information theory; and our lessons learned, which hopefully can inspire future research.},
url = {http://approjects.co.za/?big=en-us/research/publication/ease-ml-a-lifecycle-management-system-for-mldev-and-mlops/},
}