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Keynote Lectures

Federated Learning, Knowledge Transfer, and Knowledge Distillation: Developments with Information Granules
Witold Pedrycz, University of Alberta, Canada

Breathing Life into Models: The Next Generation of Enterprise Modeling
Peter Fettke, German Research Center for Artificial Intelligence (DFKI) and Saarland University, Germany

Program Verification: A 70+-Year History
Moshe Y. Vardi, Rice University, United States

 

Federated Learning, Knowledge Transfer, and Knowledge Distillation: Developments with Information Granules

Witold Pedrycz
University of Alberta
Canada
 

Brief Bio
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. 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, a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society, and 2019 Meritorious Service Award from the IEEE Systems Man and Cybernetics Society.
His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks, and control engineering. He has published papers in these areas. He is also an author of 21 research monographs and edited volumes covering various aspects of Computational Intelligence, data mining, and Software Engineering.
Dr. Pedrycz is vigorously 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 Co-editor-in-Chief of Int. J. of Granular Computing (Springer) and J. of Data Information and Management (Springer). He serves on an Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of international journals.


Abstract
The visible trends of Machine Learning addressing the emerging needs of coping with the diversity of real-world motivated learning scenarios involve federated learning, transfer learning, and knowledge distillation.
We advocate that to conveniently address these challenges encountered in these directions, it becomes beneficial to engage the fundamental framework of Granular Computing to enhance the above approaches or to establish new and augmented methodologies. We demonstrate that various ways of conceptualization of information granules in the form of fuzzy sets, sets, rough sets, among others, lead to efficient solutions.
To establish a sound conceptual modeling framework, we include a brief discussion of concepts of information granules and Granular Computing. In the sequel, a concise information granules-oriented design of rule-based architectures is discussed. A way of forming the rules through unsupervised federated learning is investigated along with algorithmic developments. A granular characterization of the model formed by the server vis-a-vis data located at individual clients is presented. It is demonstrated that the quality of the rules at the client’s end is described in terms of granular parameters and subsequently the global model becomes represented as a granular model. Subsequently, the roles of granular augmentations of models in the setting of granular knowledge transfer and knowledge distillation, in particular, are discussed.



 

 

Breathing Life into Models: The Next Generation of Enterprise Modeling

Peter Fettke
German Research Center for Artificial Intelligence (DFKI) and Saarland University
Germany
 

Brief Bio
Dr. Peter Fettke is Professor of Business Informatics at Saarland University and Principal Researcher, Research Fellow and Research Group Leader at the German Research Centre for Artificial Intelligence (DFKI) in Saarbrücken, Germany. In his application-oriented basic research and basic-oriented applied research, he and his research group of around 30 people address questions at the interface of the disciplines of business informatics and artificial intelligence (AI), in particular the modeling of computer-integrated systems, systems mining, process predictions, and robotic process automation. His work is among the most cited articles in leading international journals on business informatics and he is one of the top 5 most cited scientists at DFKI (more than 250 peer-reviewed publications, more than 10,000 citations, h-index 40). He is Co-Editor-in-Chief of the journal "Enterprise Modelling and Information Systems Architectures" (EMISAJ). Peter founded the DFKI-based "Center of Competence for Tax Technology" and "Competence Center for Audit Transformation". He is also a sought-after reviewer for renowned conferences, journals, and research organisations.


Abstract
Edsger W. Dijkstra has frequently suggested building a “firewall” between the technology- and application side of computer science. His justification: The methods to attack the computer scientists’ formal, mathematical “correctness problem” differ fundamentally from the methods to attack the applicants’ informal “pleasantness problem”. In this setting, a model is always confined to one side or the other of this wall. This keynote shows that a seamless transition between both sides can be achieved by a framework with architecture, statics, and dynamics as the three pillars of modeling computer-integrated systems. Selected examples justify this framework. It allows to “breath life” into (static) models, and it implies a new understanding of the “pleasantness” of computer-integrated systems, which is well-needed in the age of “digital first”.



 

 

Program Verification: A 70+-Year History

Moshe Y. Vardi
Rice University
United States
 

Brief Bio
Moshe Y. Vardi is University Professor and the George Distinguished Service Professor in Computational Engineering at Rice University. He is the recipient of several awards, including the ACM SIGACT Goedel Prize, the ACM Kanellakis Award, the ACM SIGMOD Codd Award, the Knuth Prize, the IEEE Computer Society Goode Award, and the EATCS Distinguished Achievements Award. He is the author and co-author of over 700 papers, as well as two books. He is a Guggenheim Fellows as well as fellow of several societies, and a member of several academies, including the US National Academy of Engineering and National Academy of Science. He holds seven honorary doctorates. He is a Senior Editor of the Communications of the ACM, the premier publication in computing.


Abstract
The year 2019 saw the 70th anniversary to Alan Turing's 1949 paper, "Checking a Large Routine" and the 50th anniversary of Tony Hoare's paper, "An Axiomatic Basis for Computer Programming". In the latter paper, Hoare stated: "When the correctness of a program, its compiler, and the hardware of the computer have all been established with mathematical certainty, it will be possible to place great reliance on the results of the program, and predict their properties with a confidence limited only by the reliability of the electronics."

In this talk, I will review the history of this vision, describing the obstacles, the controversies, and progress milestones. I will conclude with the description of both impressive progress and dramatic failures exhibited over the past few years.



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