Nov 10, 2016
Talk by Prof. Witold Pedrycz, IEEE Fellow
Title: Granular Computing in Data Analytics
Abstract: The apparent challenges in data analytics inherently associate with large volumes of data, data variability, and an evident quest for transparency and interpretability of obtained results. We advocate that information granules play a pivotal role in addressing these key challenges. We demonstrate that a framework of Granular Computing along with a diversity of its formal settings offers a badly needed conceptual and algorithmic environment that becomes instrumental for data analytics.
We elaborate on selected ways in which information granules and their processing address help in coping with abundance of data. A suitable perspective built with the aid of information granules is advantageous in realizing a suitable level of abstraction and forming sound, problem-oriented tradeoffs among precision of results, easiness of their interpretation, value of the results and their stability. All those aspects emphasize importance of actionability and interestingness of the produced findings.
Discussed are ways of forming information granules carried out on a basis of abundant data with the mechanisms of information granulation applied to the reduction of amount of data and dimensionality of data. The development of information granules of higher type and higher order is advocated and their unique role in realizing a hierarchy of processing and coping with a distributed nature of available data is presented. The detailed investigations are focused on selected problems of (i) building auto-encoders in architectures of deep learning and (ii) evolution of information granules in describing dynamics of data streams.
Bio-sketch: Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. In 2009 Dr. Pedrycz was elected a foreign member of the Polish Academy of Sciences. In 2012 he was elected a Fellow of the Royal Society of Canada. Witold Pedrycz has been a member of numerous program committees of IEEE conferences in the area of fuzzy sets and neurocomputing. In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. He is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society.
His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data mining, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and Software Engineering. He has published numerous papers in this area. He is also an author of 15 research monographs covering various aspects of Computational Intelligence, data mining, and Software Engineering.
Dr. Pedrycz is intensively involved in editorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Int. J. of Granular Computing (Springer). He currently serves on the Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of other international journals.