LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems-Reference-Cited by-同舟云学术

LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems

Published:2021-06-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2021 International Conference on Management of Data
language:
Short-container-title:

Author:

Phani Arnab¹,Rath Benjamin¹,Boehm Matthias¹

Affiliation:

1. Graz University of Technology, Graz, Austria

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3448016.3452788

Reference111 articles.

1. Sherif Akoush Ripduman Sohan and Andy Hopper. 2013. HadoopProv: Towards Provenance as a First Class Citizen in MapReduce. In TaPP. Sherif Akoush Ripduman Sohan and Andy Hopper. 2013. HadoopProv: Towards Provenance as a First Class Citizen in MapReduce. In TaPP.

2. Putting lipstick on pig

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SAGA: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications;Proceedings of the ACM on Management of Data;2023-11-13

2. ElasticNotebook: Enabling Live Migration for Computational Notebooks;Proceedings of the VLDB Endowment;2023-10

3. Integrated Reproducibility with Self-describing Machine Learning Models;Proceedings of the 2023 ACM Conference on Reproducibility and Replicability;2023-06-27

4. Transactional Python for Durable Machine Learning: Vision, Challenges, and Feasibility;Proceedings of the Seventh Workshop on Data Management for End-to-End Machine Learning;2023-06-18

5. Federated Data Preparation, Learning, and Debugging in Apache SystemDS;Proceedings of the 31st ACM International Conference on Information & Knowledge Management;2022-10-17