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Los desafíos de la modelización hidrológica y la previsión de crecidas en tiempo real en alta montaña
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A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...
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Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...
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2023Budget-Bounded Incentives for Federated Learning
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Springer Nature Switzerland AG 20202022Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data
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Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...
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Urban air quality is a major concern in the context of human health since cities are at the same time emission hot spots and home to a large fraction of the world's population. Airborne imaging spectrometers may be a valuable addition to traditional air po ...
EPFL2022Pollution Detection Algorithm (PDA)
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The Pollution Detection Algorithm (PDA) is an algorithm to identify and flag periods of primary polluted data in remote atmospheric time series in five steps. The first and most important step identifies polluted periods based on the gradient (time-derivat ...
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Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological ...
SAGE PUBLICATIONS INC2021Spatio-temporal controls of C–N–P dynamics across headwater catchments of a temperate agricultural region from public data analysis
Characterizing and understanding spatial variability in water quality for a variety of chemical elements is an issue for present and future water resource management. However, most studies of spatial variability in water quality focus on a single element a ...
2021