Arnaud Joly

Random forests with random projections of the output space for high dimensional multi-label classification

We adapt the idea of random projections applied to the output space, so as to enhance tree-based ensemble methods in the context of multi-label classification. We show how learning time complexity can be reduced without affecting computational complexity and accuracy of predictions. We also show that random output space projections may be used in order to reach different bias-variance tradeoffs, over a broad panel of benchmark problems, and that this may lead to improved accuracy while reducing significantly the computational burden of the learning stage.

Simple connectome inference from partial correlation statistics in calcium imaging

This book illustrates the thrust of the scientific community to use machine learning concepts for tackling a complex problem: given time series of neuronal spontaneous activity, which is the underlying connectivity between the neurons in the network? The contributing authors also develop tools for the advancement of neuroscience through machine learning techniques, with a focus on the major open problems in neuroscience. While the techniques have been developed for a specific application, they address the more general problem of network reconstruction from observational time series, a problem of interest in a wide variety of domains, including econometrics, epidemiology, and climatology, to cite only a few. The book is designed for the mathematics, physics and computer science communities that carry out research in neuroscience problems. The content is also suitable for the machine learning community because it exemplifies how to approach the same problem from different perspectives.

Erratum: Elevated basal levels of circulating activated platelets predict ICU-acquired sepsis and mortality: a prospective study.

Platelets are now considered to be immune and inflammatory agents as well as key cells in coagulation, and as such have been implicated in the pathophysiology of sepsis [1]. Thrombocytopenia is associated with sepsis severity and poor prognosis, and hyperactivated platelets probably contribute to microvascular thrombosis and organ failure. In the present study, we evaluated platelet activation markers as potential predictive markers of sepsis and of mortality among four commonly encountered populations of patients admitted to ICUs.

Erratum: Prospective immune profiling in critically ill adults: before, during and after severe sepsis and septic shock.

Author details Department of General Intensive Care, University Hospital Centre of Liege, Domaine Sart-Tilman B35, Liege 4000, Belgium. GIGA-Cardiovascular Sciences, Laboratory of Thrombosis and Hemostasis, University of Liege, Domaine Sart-Tilman B35, 4000 Liege, Belgium. CHU de Liege, Domaine Sart-Tilman B35, 4000 Liege, Belgium. Laboratory Hematology, University Hospital Centre of Liege, Liege, Belgium. Systems and Modeling, Department of Electrical Engineering and Computer Science and GIGA-R, University of Liege, Domaine Sart-Tilman B35, 4000 Liege, Belgium. Reference 1. Layios N. Prospective immune profiling in critically ill adults: before, during and after severe sepsis and septic shock. Crit Care. 2015;19(Suppl 1):P43.