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View all- Werder KRamesh BZhang R(2022)Establishing Data Provenance for Responsible Artificial Intelligence SystemsACM Transactions on Management Information Systems10.1145/350348813:2(1-23)Online publication date: 10-Mar-2022
Empirical evidence shows that in favorable situations semi-supervised learning (SSL) algorithms can capitalize on the abundance of unlabeled training data to improve the performance of a learning task, in the sense that fewer labeled training data are ...
This paper investigates booststrapping part-of-speech taggers using co-training, in which two taggers are iteratively re-trained on each other's output. Since the output of the taggers is noisy, there is a question of which newly labelled examples to ...
Association for Computing Machinery
New York, NY, United States
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