Complaint-driven Training Data Debugging for Query 2.0-Reference-Cited by-同舟云学术

Complaint-driven Training Data Debugging for Query 2.0

Published:2020-06-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
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Author:

Wu Weiyuan¹,Flokas Lampros²,Wu Eugene²,Wang Jiannan¹

Affiliation:

1. Simon Fraser University, Burnaby, BC, Canada

2. Columbia University, New York, NY, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3318464.3389696

Reference85 articles.

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2. Detecting data errors

3. DIFF;Abuzaid Firas;A Relational Interface for Large-Scale Data Explanation. Proc. VLDB Endow.,2018

4. Ashvin Agrawal Rony Chatterjee Carlo Curino Avrilia Floratou Neha Gowdal Matteo Interlandi Alekh Jindal Konstantinos Karanasos Subru Krishnan Brian Kroth Jyoti Leeka Kwanghyun Park Hiren Patel Olga Poppe Fotis Psallidas Raghu Ramakrishnan Abhishek Roy Karla Saur Rathijit Sen Markus Weimer Travis Wright and Yiwen Zhu. 2019. Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. CoRR (2019). http://arxiv.org/abs/1909.00084 Ashvin Agrawal Rony Chatterjee Carlo Curino Avrilia Floratou Neha Gowdal Matteo Interlandi Alekh Jindal Konstantinos Karanasos Subru Krishnan Brian Kroth Jyoti Leeka Kwanghyun Park Hiren Patel Olga Poppe Fotis Psallidas Raghu Ramakrishnan Abhishek Roy Karla Saur Rathijit Sen Markus Weimer Travis Wright and Yiwen Zhu. 2019. Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. CoRR (2019). http://arxiv.org/abs/1909.00084

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