Showing 101 - 120 results of 499 for search 'explicit performance information', query time: 0.11s Refine Results
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    Quantum key distribution as a quantum machine learning task by Thomas Decker, Marcelin Gallezot, Sven Florian Kerstan, Alessio Paesano, Anke Ginter, Wadim Wormsbecher

    Published 2025-08-01
    “…QKD protocols are well understood and solid security proofs exist enabling an easy evaluation of the QML model performance. The power of easy-to-implement QML techniques is shown by finding the explicit circuit for optimal individual attacks in a noise-free setting. …”
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  3. 103

    Hand-aware graph convolution network for skeleton-based sign language recognition by Juan Song, Huixuechun Wang, Jianan Li, Jian Zheng, Zhifu Zhao, Qingshan Li

    Published 2025-01-01
    “…With the aim to further improve the performance, the joints information, bones, together with their motion information are simultaneously modeled in a multi-stream framework. …”
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    A Semantically Enhanced Label Prediction Method for Imbalanced POI Data Category Distribution by Hongwei Zhang, Qingyun Du, Shuai Zhang, Renfei Yang

    Published 2024-10-01
    “…Simultaneously, POI data labels are introduced to provide explicit semantic information, and the semantic relationship between POI data labels and their names is determined using cross-coding. …”
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    BGNER: A boundary guidance framework for enhanced named entity recognition by Yu He, Li Sun, Qianyu Yue, Haitao Wu, Xiaojuan Wang

    Published 2025-06-01
    “…However, these approaches often fail to fully leverage boundary information, as they classify spans independently without explicitly incorporating the context immediately outside the span boundaries. …”
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    A Deep Learning Framework for Enhancing Recommender Systems With Dual-Feedback Integration by V. Lakshmi Chetana, Hari Seetha

    Published 2025-01-01
    “…Traditional CF approaches often struggle with sparsity, necessitating the development of hybrid methods that integrate both explicit and implicit feedback to enhance performance. …”
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  17. 117

    DREAM3: network inference using dynamic context likelihood of relatedness and the inferelator. by Aviv Madar, Alex Greenfield, Eric Vanden-Eijnden, Richard Bonneau

    Published 2010-03-01
    “…<h4>Methodology</h4>We aim to investigate whether scalable information based methods (like the Context Likelihood of Relatedness method) and more explicit dynamical models (like Inferelator 1.0) prove synergistic when combined. …”
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