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Paolo Pellizzoni, Andrea Pietracaprina and Geppino Pucci
Metric k-center clustering is a fundamental unsupervised learning primitive. Although widely used, this primitive is heavily affected by noise in the data, so a more sensible variant seeks for the best solution that disregards a given number z of points ...
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Hailun Xia and Tianyang Zhang
Estimating the positions of human joints from monocular single RGB images has been a challenging task in recent years. Despite great progress in human pose estimation with convolutional neural networks (CNNs), a central problem still exists: the relation...
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Leonid Safonov
Pág. 109 - 112
Unsupervised anomaly detection in high-dimensional data is an important subject of research in theoretical machine learning and applied areas. One of important applications is anomaly detection in network traffic data, which can be useful for preventing ...
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Dimitrios Loukrezis and Herbert De Gersem
Approximation and uncertainty quantification methods based on Lagrange interpolation are typically abandoned in cases where the probability distributions of one or more system parameters are not normal, uniform, or closely related distributions, due to t...
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Sungkun Hwang, Recep M. Gorguluarslan, Hae-Jin Choi and Seung-Kyum Choi
Interests in strain gauge sensors employing stretchable patch antenna have escalated in the area of structural health monitoring, because the malleable sensor is sensitive to capturing strain variation in any shape of structure. However, owing to the nar...
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