𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Learning from partially supervised data using mixture models and belief functions

✍ Scribed by E. Côme; L. Oukhellou; T. Denœux; P. Aknin

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
480 KB
Volume
42
Category
Article
ISSN
0031-3203

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Cardiac function estimation from MRI usi
Cardiac function estimation from MRI using a heart model and data assimilation: Advances and difficulties
✍ M. Sermesant; P. Moireau; O. Camara; J. Sainte-Marie; R. Andriantsimiavona; R. C 📂 Article 📅 2006 🏛 Elsevier Science 🌐 English ⚖ 963 KB

In this paper, we present a framework to estimate local ventricular myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is defo

Pure component spectral reconstruction f
Pure component spectral reconstruction from mixture data using SVD, global entropy minimization, and simulated annealing. Numerical investigations of admissible objective functions using a synthetic 7-species data set
✍ Effendi Widjaja; Marc Garland 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 217 KB

## Abstract A combination of singular value decomposition, entropy minimization, and simulated annealing was applied to a synthetic 7‐species spectroscopic data set with added white noise. The pure spectra were highly overlapping. Global minima for selected objective functions were obtained for the