Titlebook: Continual Semi-Supervised Learning; First International Fabio Cuzzolin,Kevin Cannons,Vincenzo Lomonaco Conference proceedings 2022 The Edi

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Fundamental Rules for the VR Surgeonunity via the IJCAI 2021 International Workshop on Continual Semi-Supervised Learning (CSSL@IJCAI) (.), with the aim of raising the field’s awareness about this problem and mobilising its effort in this direction. After a formal definition of continual semi-supervised learning and the appropriate tr

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The VR Surgeon’s Relation to His Nurseever new task arrives. However, existing approaches are designed in supervised fashion assuming all data from new tasks have been manually annotated, which are not practical for many real-life applications. In this work, we propose to use pseudo label instead of the ground truth to make continual le

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Damien Coyle,Kamal Abuhassan,Liam Maguireng process in machines is a challenging task, also due to the inherent difficulty in creating conditions for designing continuously evolving dynamics that are typical of the real-world. Many existing research works usually involve training and testing of virtual agents on datasets of static images o

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Damien Coyle,Kamal Abuhassan,Liam Maguirein general, capable of learning tasks sequentially. This long-standing challenge for deep neural networks (DNNs) is called .. Multiple solutions have been proposed to overcome this limitation. This paper makes an in-depth evaluation of the ., exploring the efficiency, performance, and scalability of

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https://doi.org/10.1007/978-3-319-20194-8rning objective that differentiates through a sequential learning process. Specifically, we train a linear model over the representations to match different augmented views of the same image together, each view presented sequentially. The linear model is then evaluated on both its ability to classif

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