| FUZZ-IEEE 2010 Invited Sessions |
Speakers
 Intelligent Learning Methods for Soft Computing Systems
Dr. Ronald R. Yager
Iona College, USA Tuesday, July 20 11:50h - 12:50h Abstract
In this presentation our concern is with technologies that allow the construction of intelligent learning systems. We discuss a number of technologies that support this capability: the participatory learning paradigm, the hierarchical prioritized structure and the mountain clustering method. The basic premise of the participatory learning paradigm is that learning takes place in the framework of what is already learned and believed. The implication of this is that every aspect of the learning process is affected and guided by the current belief system. This name, participatory learning, highlights the fact that in learning we are in a situation in which the current knowledge of what we are trying to learn participates in the process of learning about itself. The hierarchical prioritized structure provides a generalization of fuzzy systems modeling by introducing a hierarchical representation of the rules. It supports systems evolution by allowing the learning of new rules based and their insertion at different levels of the hierarchy. Short Biography
Ronald R. Yager has worked in the area of machine intelligence for over twenty-five years. He has published over 500 papers and fifteen books in areas related to fuzzy sets, decision making under uncertainty and the fusion of information. He is among the world's top 1% most highly cited researchers with over 7000 citations. He was the recipient of the IEEE Computational Intelligence Society Pioneer award in Fuzzy Systems. Dr. Yager is a fellow of the IEEE, the New York Academy of Sciences and the Fuzzy Systems Association. He was given a lifetime achievement award by the Polish Academy of Sciences for his contributions. He served at the National Science Foundation as program director in the Information Sciences program. He was a NASA/Stanford visiting fellow and a research associate at the University of California, Berkeley. He has been a lecturer at NATO Advanced Study Institutes. He is a distinguished honorary professor at the Aalborg University Denmark. He is an affiliated distinguished researcher at the European Centre for Soft Computing. He received his undergraduate degree from the City College of New York and his Ph. D. from the Polytechnic University of New York. Currently, he is Director of the Machine Intelligence Institute and Professor of Information Systems at Iona College. He is editor and chief of the International Journal of Intelligent Systems. He serves on the editorial board of numerous technology journals.  Some New Indices for Relational Cluster Validity
Dr. James C. Bezdek
University of Florida, USA Wednesday, July 21 11:50h - 12:50h Abstract
This talk is about validation of partitions found by clustering in square relational data. The new methods are relatives of three well-known validity indices: (i) Hubert's modified Gamma statistic; (ii) the generalized Dunn indices; and (iii) the extended Xie-Beni index. Some theoretical results are presented, and then we provide numerical examples that illustrate various facets of the new indices. The data used in our experiments are relational data of two types: (i) dissimilarity data induced by computing pairwise Euclidean distances on object data sets; and (ii) pure relational data, i.e., relational data without object vector data analogues, that directly represent pairwise object similarities. Short Biography
Dr. James C. Bezdek received the PhD in Applied Mathematics from Cornell University in 1973. Jim is past president of NAFIPS (North American Fuzzy Information Processing Society), IFSA (International Fuzzy Systems Association) and the IEEE CIS (Computational Intelligence Society): founding editor the International Journal Approximate Reasoning and the IEEE Transactions on Fuzzy Systems: fellow of the IEEE and IFSA; and a recipient of the IEEE 3rd Millennium, IEEE CIS Fuzzy Systems Pioneer, and IEEE CIS Rosenblatt medals. Jim's interests: woodworking, optimization, motorcycles, pattern recognition, cigars, clustering in very large data, fishing, poker, co-clustering, blues music, and visual clustering in relational data. Jim retired in 2007, and will be coming to a university near you soon.  Competitive Clustering for Multimedia Mining and Retrieval
Dr. Nozha Boujemaa
INRIA (Paris-Rocquencourt), France Friday, July 23 11:30h - 12:30h Abstract
Clustering and grouping is essential for several visual-content indexing and retrieval tasks within a multimedia search engine. This talk is about discussing diverse clustering methods for image collection summarization and browsing based on visual signatures feature space. Starting from generalization of competitive clustering algorithm, relational clustering for local features vectors with different dimensions till active semi-supervised clustering, the presentation will cover several information retrieval problems: gene expression studies, mental image search... Since, fully automatic categories do not reflect user expectations, the active semi-supervised clustering allow the integration of user knowledge through pair-wise constraints into the optimization process. User constraints, actively selected, indicate how different the perceptual similarity space is from the feature space. Such method is related to active learning approaches where the success criteria are measured by the ability to reach high performance from few user interactions. Large scale and real time clustering are challenging issues to go further with multimedia search engines. Short Biography
Dr. Nozha Boujemaa is a director of research at INRIA (Paris-Rocquencourt), the French national institute for research in computer science and control, and head of the IMEDIA research group. She obtained her PhD in computer science in 1993 and her "Habilitation à Diriger des Recherches" in computer science in 2000. Her topics of interests include Multimedia Content Search, Pattern Recognition and Machine Learning. She develops methods for automatic visual content enrichment, non exclusive clustering, organising and browsing visual content together with interactive and personalized information retrieval mechanisms. She has published over 150 papers in international journals and conference proceedings. She has also supervised over 30 PhD and master students. She has served on numerous scientific program committees in international conferences. She is the General Chair of ACM Multimedia Information Retrieval 2010, Chair of "Brave New Ideas" program within ACM Multimedia 2010. She's also a member of the Steering Committee of the ACM International Conference of Multimedia Information Retrieval (2008-2012). She serves as the scientific coordinator for several European projects: "Multimedia Understanding through Semantics, Computation and Learning" European Network of Excellence, CHORUS Coordination Action on multimedia search engines and the VITALAS project: "Video & image Indexing and Retrieval in the Large Scale". She is involved in other international and national projects covering several application areas such as audio-visual archives, photo stocks agency, biodiversity, satellite images and security. She has served as a scientific expert for numerous international bodies such as the National Science Foundation and the European Commission as well as French National Parliament Assembly (Law on Digital Economy). Links |
