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Immutable vectors are a convenient data structure for functional programming and part of the standard library of modern languages like Clojure and Scala. The common implementation is based on wide trees with a fixed number of children per node, which allow ...
Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, ...
The level of dexterity of myoelectric hand prostheses depends to large extent on the feature representation and subsequent classification of surface electromyography signals. This work presents a comparison of various feature extraction and classification ...
Machine learning has been largely applied to ana- lyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines ...
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We extend Clarkson's framework by considering parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an ε-approximate solution (and a corresponding ε-coreset) ...
The goal of the Computers in Cardiology / Physionet Challenge 2009 is to predict which patients will experience acute hypotensive episode within a forecast window of one hour. In our study, statistically robust features extracted from the supplied training ...
We are witnessing a growing interest in Networks on Chips (NoC) that is related to the evolution of integrated circuit technology and to the growing requirements in performance and portability of electronic systems. Current integrated circuits contain seve ...
Support vector machines (SVMs) are one of the most successful algorithms for classification. However, due to their space and time requirements, they are not suitable for on-line learning, that is, when presented with an endless stream of training observati ...
Classifying materials from their appearance is challenging. Impressive results have been obtained under varying illumination and pose conditions. Still, the effect of scale variations and the possibility to generalise across different material samples are ...
Distributed compressed sensing is the extension of compressed sampling (CS) to sensor networks. The idea is to design a CS joint decoding scheme at a central decoder (base station) that exploits the inter-sensor correlations, in order to recover the whole ...
