Addressing the cold start problem in active learning using self-supervised learning

Addressing the cold start problem in active learning using self-supervised learning

Active learning promises to improve annotation efficiency by iteratively selecting the most important data to be annotated first. However, we uncover a striking contrast to this promise: Active querying strategies fail to select data as effectively as random selection at the first choice. We identif...

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書目詳細資料
主要作者:	Chen, Liangyu
其他作者:	Wen Bihan
格式:	Final Year Project
語言:	English
出版:	Nanyang Technological University 2022
主題:	Engineering::Electrical and electronic engineering
在線閱讀:	https://hdl.handle.net/10356/158461
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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