@inproceedings{jafarpour-etal-2021-active,
    title = "Active Curriculum Learning",
    author = "Jafarpour, Borna  and
      Sepehr, Dawn  and
      Pogrebnyakov, Nick",
    editor = {Brantley, Kiant{\'e}  and
      Dan, Soham  and
      Gurevych, Iryna  and
      Lee, Ji-Ung  and
      Radlinski, Filip  and
      Sch{\"u}tze, Hinrich  and
      Simpson, Edwin  and
      Yu, Lili},
    booktitle = "Proceedings of the First Workshop on Interactive Learning for Natural Language Processing",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.internlp-1.6/",
    doi = "10.18653/v1/2021.internlp-1.6",
    pages = "40--45",
    abstract = "This paper investigates and reveals the relationship between two closely related machine learning disciplines, namely Active Learning (AL) and Curriculum Learning (CL), from the lens of several novel curricula. This paper also introduces Active Curriculum Learning (ACL) which improves AL by combining AL with CL to benefit from the dynamic nature of the AL informativeness concept as well as the human insights used in the design of the curriculum heuristics. Comparison of the performance of ACL and AL on two public datasets for the Named Entity Recognition (NER) task shows the effectiveness of combining AL and CL using our proposed framework."
}