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Recently Added 

  1. Interpretable representations in explainable AI: from theory to practice 

    Sokol, Kacper; Flach, Peter (2024)
    Data Mining and Knowledge Discovery
    Interpretable representations are the backbone of many explainers that target black-box predictive systems based on artificial intelligence and machine learning algorithms. They translate the low-level data representation necessary for good predictive performance into high-level human-intelligible concepts used to convey the explanatory insights. Notably, the explanation type and its cognitive complexity are directly controlled by the ...
    Journal Article
  2. Epidermal visualized health monitoring system based on stretchable and washable TPU hybrid conductive microtextiles 

    Yuan, Jing-Bo; Feng, Zhi-Hong; Li, Dong-Chan; et al. (2024)
    Rare Metals
    Electronic textiles, an emerging class of electronic technology, offer exciting opportunities for seamless integration with the human body. Numerous applications have been developed based on electronic textiles. However, researches on integrating multiple electronic textile-based devices are still few. In this study, we present a system integrated with an electrocardiogram monitoring sensor and an electroluminescence device based on ...
    Journal Article
  3. Precise QCD predictions for W-boson production in association with a charm jet 

    Ridder, A. Gehrmann-De; Gehrmann, T.; Glover, E. W. N.; et al. (2024)
    The European Physical Journal C
    The production of a W-boson with a charm quark jet provides a highly sensitive probe of the strange quark distribution in the proton. Employing a novel flavour dressing procedure to define charm quark jets, we compute W+charm-jet production up to next-to-next-to-leading order (NNLO) in QCD. We study the perturbative stability of production cross sections with same-sign and opposite-sign charge combinations for the W boson and the charm ...
    Journal Article
  4. Data Summarization via Bilevel Optimization 

    Borsos, Zalan; Mutny, Mojmir; Tagliasacchi, Marco; et al. (2024)
    Journal of Machine Learning Research
    The increasing availability of massive data sets poses various challenges for machine learning. Prominent among these is learning models under hardware or human resource straints. In such resource -constrained settings, a simple yet powerful approach is operating on small subsets of the data. Coresets are weighted subsets of the data that provide approximation guarantees for the optimization objective. However, existing coreset constructions ...
    Journal Article

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