Titlebook: Artificial Intelligence and Machine Learning; 33rd Benelux Confere Luis A. Leiva,Cédric Pruski,Christoph Schommer Conference proceedings 20

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https://doi.org/10.1007/978-3-658-45166-0 more complex tasks, but not vice versa. We have also studied which part of the knowledge is most important for transfer to succeed, and identify which layers should be used for pre-training (Codes we used for this work can be found at .).

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Balaraman Deivasigamani,Ann Suji Hudsonlting recommitment policy is compared to state-of-the-art strategies. Numerical results suggest that the trained policy can achieve high target allocation while bounding the risk of being overinvested.

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Active Learning for Reducing Labeling Effort in Text Classification Tasks Furthermore, we explore the influence of the query-pool size on the performance of AL. Whereas it was found that the proposed heuristics for AL did not improve performance of AL; our results show that using uncertainty-based AL with BERT. outperforms random sampling of data. This difference in perf

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