Books F. Scalzo. Learning Visual Feature Hierarchies. VDM Verlag, ISBN 978-3-639-18002-2, July, 2009. Jounal Papers F. Scalzo, P. Xu, S. Asgari, M. Bergsneider, X. Hu. Regression Analysis for Peak Designation in Pulsatile Pressure Signals. Medical & Biological Engineering & Computing, July, 2009. X. Hu, P. Xu, F. Scalzo, P. Vespa, M. Bergsneider. Morphological Clustering and Analysis of Continuous Intracranial Pressure. IEEE Transactions on Biomedical Engineering, 56(3):696-705, March, 2009. Conference Papers F. Scalzo. Unsupervised Learning of Generative Factor Graph Hierarchies. ICML Workshop on Learning Feature Hierarchies, 2009 (Montreal, Canada). F. Scalzo, P. Xu, M. Bergsneider, X. Hu. Random Subwindows for Robust Peak Recognition in Intracranial Pressure Signals. International Symposium on Visual Computing (ISVC), 2008 (Las Vegas, USA). (Oral) C. Sarkiss, X. Hu, F. Scalzo, T. Glenn, N. Martin. Predicting Cerebral Blood Flow Based on a Multimodal Approach. UCLA Josiah Brown Poster Fair 2008. F. Scalzo, P. Xu, M. Bergsneider, X. Hu. Morphological Feature Extraction of Intracranial Pressure Signals via Nonlinear Regression. Benelearn 2008 (Spa, Belgium). F. Scalzo, P. Xu, M. Bergsneider, X. Hu. Nonlinear Regression For Sub-Peak Detection of Intracranial Pressure Signals. IEEE Int. Conf. Engineering and Biology Society, 2008 (EMBC, Vancouver, Canada). (Oral) P. Xu, F. Scalzo, M. Bergsneider, X. Hu. Wavelet Entropy Characterization of Elevated Intracranial Pressure. IEEE Int. Conf. Engineering and Biology Society, 2008 (EMBC, Vancouver, Canada). F. Scalzo, G. Bebis, M. Nicolescu, L. Loss, A. Tavakkoli. Feature Fusion Hierarchies for Gender Classification. Proc. of the International Conference on Pattern Recognition (ICPR), 2008 (Tampa, Florida). J. Piater, F. Scalzo, and R. Detry. Hierarchical Markov Network for Object Recognition. Benelearn 2008 (Spa, Belgium). F. Scalzo, G. Bebis, M. Nicolescu, L. Loss. Evolutionary Learning of Feature Fusion Hierarchies. Benelearn 2008 (Spa, Belgium). J. Piater, F. Scalzo, and R. Detry. Vision as Inference in a Hierarchical Markov Network. ICCNS, 2008 (Boston, USA). F. Scalzo, J. Piater, Adaptive patch features for object class recognition with learned hierarchical models. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Beyond Patches Workshop), 2007 (Minneapolis, MN, USA). F. Scalzo, J. Piater, Unsupervised Learning of Dense Hierarchical Appearance Representations. Proc. of the International Conference on Pattern Recognition (ICPR), 2006 (Hong-Kong, China). F. Scalzo, J. Piater, Combining Generative and Discriminative Learning of Feature Hierarchies for Object Recognition. Research Contact Day of the CIL doctoral school, 2006 (Brussels, Belgium). F. Scalzo, J. Piater. Statistical learning of visual feature hierarchies. Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition (CVPR), 2005. S. Jodogne, F. Scalzo, J. Piater. Task-Driven Learning of Spatial Combinations of Visual Features. Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition (CVPR), 2005. F. Scalzo, J. Piater. Unsupervised Learning of Visual Feature Hierarchies. Proc. of the International Conference on Machine Learning and Data Mining (MLDM), 2005. F. Scalzo. Apprentissage Non-Supervise de Caracteristiques Visuelles. ORASIS 2005 (Fournol, France). Thesis F. Scalzo. Learning Visual Feature Hierarchies. PhD Thesis. University of Liege, Belgium. 2007-2008.