| Title: | Bayesian Surprise Attracts Human Attention |
| Date: |
October 10, 2005 (Monday)
|
| Time: |
4:30 p.m. - 5:30 p.m.
|
| Venue: |
TYW LT, 5/F, Ho Sin Hang Engineering Building,
The Chinese University of Hong Kong, Shatin, N.T. |
| Speaker: |
Professor Pierre Baldi
School of Information and Computer Sciences Department of Biological Chemistry Director Institute for Genomics and Bioinformatics University of California, Irvine USA |
The concept of surprise is central to sensory processing, adaptation and learning, attention, and decision making. Yet, no widely-accepted mathematical theory currently exists to quantitatively characterize surprise elicited by a stimulus or event, for observers that range from single neurons to complex natural or engineered systems. We describe a formal Bayesian definition of surprise that is the only consistent formulation under minimal axiomatic assumptions. Surprise quantifies how data affects a natural or artificial observer, by measuring the difference between posterior and prior beliefs of the observer. Using this framework we measure the extent to which humans direct their gaze towards surprising items while watching television and video games. Humans are strongly attracted to locations of high Bayesian surprise, with 720f all human gaze shifts directed towards locations more surprising than the average, a figure which rises to 84% when considering only gaze targets simultaneously selected by all subjects. The resulting theory of surprise is applicable across different spatio-temporal scales, modalities, and levels of abstraction.
BIOGRAPHY:
Pierre Baldi is a Professor in the School of Information and Computer Sciences and the Department of Biological Chemistry at the University of California, Irvine and the Director of the Institute for Genomics and Bioinformatics. Born and raised in Europe, he received his PhD from the California Institute of Technology in 1986. He has held postdoctoral, faculty, and member of the technical staff positions at UCSD and Caltech, in the Division of Biology and the Jet Propulsion Laboratory. He was CEO of a startup company for a few years and joined UCI in 1999. He is the recipient of a 1993 Lew Allen Award at JPL and a Laurel Wilkening Faculty Innovation Award at UCI. Dr. Baldi's has published four books: Modeling the Internet and the We--Probabilistic Methods and Algorithms, Wiley, (2003); DNA Microarrays and Gene Regulation--From Experiments to Data Analysis and Modeling, Cambridge University Press, (2002); The Shattered Self--The End of Evolution, MIT Press, (2001); Bioinformatics: the Machine Learning Approach, MIT Press, Second Edition (2001); and over 150 scientific articles. His research focuses in various areas at the intersection of computational and life sciences, in particular the application of AI/statistical/machine learning methods to problems in bio and chemical informatics. The work of his group has resulted in several databases, software, and web servers that are widely used (www.igb.uci.edu/servers/servers.html). His main contributions include the development of Hidden Markov Models (HMMPro) for sequence analysis, recursive neural networks for de novo protein structure prediction (SCRATCH), Bayesian statistical methods for DNA microarray analysis (Cyber-T), informatics infrastructure for systems biology (SIGMOID) and, more recently, databases and tools in chemical informatics (ChemDB) for the prediction of molecular properties and applications in chemical synthesis, discovery, and drug design.
Enquiries: Miss Temmy So at tel 2609 8444
For more information, please refer to http://www.cse.cuhk.edu.hk/seminar