A Calibrated Ensemble Algorithm to Address Data Heterogeneity in Machine Learning: An Application to Identify Severe SLE Flares in Lupus Patients

Motivated to address the inconsistency between the essential i.i.d.assumption in machine learning theory and the data heterogeneity in real-world applications, we propose a novel calibrated ensemble (CE) algorithm to facilitate learning with diverse data subgroups.Unlike the traditional ensemble framework in which each learner is trained independen

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Modelling virus spreading in ride-pooling networks

Abstract Urban mobility needs alternative sustainable travel modes to keep our pandemic cities in motion.Ride-pooling, where a single vehicle is shared by more than one traveller, is not only appealing for mobility platforms and their travellers, but also for promoting the sustainability of urban mobility systems.Yet, the potential of ride-pooling

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Photon isolation and jet substructure

Abstract We introduce soft drop isolation, a new photon isolation criterion inspired by jet substructure techniques.Soft drop isolation is collinear safe and is equivalent to Frixione isolation at leading non-trivial order in the small R limit.However, soft drop isolation has the interesting feature of being democratic, meaning that photons can be

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