Mr Giorgio Roffo
- Research Associate (Computing Science)
telephone: +44 141 330 1651
My primary research interests are in the area of pattern recognition and machine learning. Within these areas, my work focuses on developing novel strategies to formalize, explain and visualize the pattern in data. I spent my Ph.D. exploring the role of ranking in machine learning applications. The rationale behind this fact is that many machine learning problems are by nature ranking problems. For example, applications in information retrieval, biometric authentication and verification, recommendation, and even in feature selection where, basically, the goal is to produce ranked lists of features to defy the curse of dimensionality and improve learning. Therefore, in some cases ranking can be used to improve machine learning, while in some other ones, learning is used to rank objects (e.g., items or any other variables) according to their degrees of relevance, preference, or importance as defined in the specific application.
Personal website: http://giorgioroffo.uk
nVIDIA GPU Grant 2017. NVIDIA GPU grants are intended to enable researchers to begin a new project and/or gain the preliminary results to support a larger proposal to other funding agencies (see GPU Grant Program).
- Discrete time Evolution Process Descriptor for shape analysis and matching. S. Melzi, M. Ovsjanikov, G. Roffo, M. Cristani, U. Castellani. ACM Transactions on Graphics, TOG, 2017.
- Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality. G. Roffo, S. Melzi. Springer Book Chapter: New Frontiers in Mining Complex Patterns, 2017.
- Infinite Feature Selection. G. Roffo, S. Melzi and M. Cristani. In Conf. IEEE International Conference on Computer Vision (ICCV 2015).
- The Visual Object Tracking VOT2016 Challenge Results. M. Kristan, A. Leonardis, J. Matas, M. Felsberg, R. Pflugfelder, G. Roffo, et Al. In Conf. IEEE European Conference on Computer Vision, Lecture Notes in Computer Science, vol 9914. Springer, 2016.
- Statistical Analysis of Personality and Identity in Chats Using a Keylogging Platform. G. Roffo, C. Giorgetta, R. Ferrario, W. Riviera and M. Cristani. In Conf. ACM International Conference on Multimodal Interaction (ICMI 2014).
- Reading Between the Turns: Statistical Modeling for Identity Recognition and Verification in Chats. G. Roffo, C. Segalin, V. Murino and M. Cristani. In Conf. IEEE Advanced Video and Signal-Based Surveillance (AVSS 2013).
- Conversationally-inspired stylometric features for authorship attribution in instant messaging. M. Cristani, G. Roffo, C. Segalin, L. Bazzani, A. Vinciarelli, and V. Murino. In Conf. ACM international conference on Multimedia, (ACMM 2012).