PASCAL – Pattern Analysis, Statistical Modelling and Computational Learning
The objective is to build a Europe-wide Distributed Institute which will pioneer principled methods of pattern analysis, statistical modelling and computational learning as core enabling technologies for multimodal interfaces that are capable of natural and seamless interaction with and among individual human users.
At each stage in the process, machine learning has a crucial role to play. It is proving an increasingly important tool in Machine Vision, Speech, Haptics, Brain Computer Interfaces, Information Extraction and Natural Language Processing; it provides a uniform methodology for multimodal integration; it is an invaluable tool in information extraction; while on-line learning provides the techniques needed for adaptively modelling the requirements of individual users. Though machine learning has such potential to improve the quality of multimodal interfaces, significant advances are needed, in both the fundamental techniques and their tailoring to the various aspects of the applications, before this vision can become a reality.
The institute will foster interaction between groups working on fundamental analysis including statisticians and learning theorists; algorithms groups including members of the non-linear programming community; and groups in machine vision, speech, haptics, brain-computer interfaces, natural language processing, information-retrieval, textual information processing and user modelling for computer human interaction, groups that will act as bridges to the application domains and end-users.
DURATION: 1 January 2005 – 28 February 2008