logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

WeShap: Weak Supervision Source Evaluation with Shapley Values

delete2024-12-01
delete0
PRE
AI
N
Naiqing Guan
N
Nick Koudas
DOI：10.14778/3717755.3717766delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Efficient data annotation stands as a significant bottleneck in training contemporary machine learning models. The Programmatic Weak Supervision (PWS) pipeline presents a solution by utilizing multiple weak supervision sources to automatically label data, thereby expediting the annotation process. Given the varied contributions of these weak supervision sources to the accuracy of PWS, it is imperative to employ a robust and efficient metric for their evaluation. This is crucial not only for understanding the behavior and performance of the PWS pipeline but also for facilitating corrective measures.

Journal

P
Proceedings of the VLDB Endowment
IF:
3.3
Papers:
556
Citations:
1.2W

Organization

No organization information available