%! Author = lukas
%! Date = 4/9/24

@InProceedings{Xu_2022_CVPR,
    author = {Xu, Yinghao and Wei, Fangyun and Sun, Xiao and Yang, Ceyuan and Shen, Yujun and Dai, Bo and Zhou, Bolei and Lin, Stephen},
    title = {Cross-Model Pseudo-Labeling for Semi-Supervised Action Recognition},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2022},
    pages = {2959-2968}
}

@online{fixmatch,
    author = "Kihyuk Sohn, David Berthelot, Chun-Liang Li",
    title = "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence",
    url = "https://arxiv.org/abs/2001.07685",
    addendum = "(accessed: 20.03.2023)",
    keywords = "FixMatch, semi-supervised"
}

@InProceedings{activelearning,
    author = "Faria, Bruno
and Perdig{\~a}o, Dylan
and Br{\'a}s, Joana
and Macedo, Luis",
    editor = "Marreiros, Goreti
and Martins, Bruno
and Paiva, Ana
and Ribeiro, Bernardete
and Sardinha, Alberto",
    title = "The Joint Role of Batch Size and Query Strategy in Active Learning-Based Prediction - A Case Study in the Heart Attack Domain",
    booktitle = "Progress in Artificial Intelligence",
    year = "2022",
    publisher = "Springer International Publishing",
    address = "Cham",
    pages = "464--475",
    abstract = "This paper proposes an Active Learning algorithm that could detect heart attacks based on different body measures, which requires much less data than the passive learning counterpart while maintaining similar accuracy. To that end, different parameters were tested, namely the batch size and the query strategy used. The initial tests on batch size consisted of varying its value until 50. From these experiments, the conclusion was that the best results were obtained with lower values, which led to the second set of experiments, varying the batch size between 1 and 5 to understand in which value the accuracy was higher. Four query strategies were tested: random sampling, least confident sampling, margin sampling and entropy sampling. The results of each approach were similar, reducing by 57{\%} to 60{\%} the amount of data required to obtain the same results of the passive learning approach.",
    isbn = "978-3-031-16474-3"
}

@inbook{Boltzmann,
    place = {Cambridge},
    series = {Cambridge Library Collection - Physical  Sciences},
    title = {Studien über das Gleichgewicht der lebendigen Kraft zwischen bewegten materiellen Punkten},
    booktitle = {Wissenschaftliche Abhandlungen},
    publisher = {Cambridge University Press},
    author = {Boltzmann, Ludwig},
    editor = {Hasenöhrl, FriedrichEditor},
    year = {2012},
    pages = {49–96},
    collection = {Cambridge Library Collection - Physical  Sciences}, key = {value},}