2020 Speakers

 

 

Keynote Speaker 1:

Prof. Assaf Schuster

ACM Fellow&IEEE Fellow, Israel Institute of Technology, Israel

 

Speech Title: Distributed Training of Deep Neural Networks

 

Abstract: Modern deep neural networks are comprised of millions and billions of parameters, which require massive amounts of data and time to train. Steady growth of these networks along the years has made it impractical to train them from scratch on a single GPU. Distributing the computations over several GPUs can drastically reduce the training time, however, stochastic gradient descent (SGD), which is typically used to train these networks, is an inherently sequential algorithm. As a result, training deep neural networks on multiple workers is difficult, especially when using non-dedicated cloud resources trying to maintain high efficiency, scalability and final accuracy. I this talk we will survey some of the new ideas in this scope and discuss their potential.

 

Biography: Prof. Assaf Schuster of the Computer Science Department is the head of the new AI center at the Technion. He is a Fellow of the ACM and the IEEE, with more than 200 published papers in highly selected venues. His interests and publications are in the wide scope of distributed and scalable data mining, big and streaming data technologies including management, analytics & prediction, cyber security and system/IoT vulnerabilities, privacy preserving, cloud resource management and more. He consulted leading hi-tech companies and participated in the bumpy journey of several startups, two of which he co-founded.

   

Keynote Speaker 2:

Prof. Xu Lei,

Fellow of IEEE, IAPR Fellow, The Chinese University of Hong Kong, China

 

Speech Title: Reasoning and Casual Computation from A Bidirectional Intelligence Perspective

 

Abstract: After a brief overview on bidirectional learning studies from the later eighties and the early nineties (e.g., autoencoder, Lmser, etc) to recent years (VAE, GAN, U-net, etc), we proceed to bidirectional intelligence, driven by long term dynamics for parameter learning and short term dynamics for image thinking and rational reasoning, including topics of (a) Why deep learning and why Lmser from a viewpoint of holistic inference vs DAG reasoning, (b) learning dependence versus discovering causal relation; (c) three levels and bidirectional framework for reasoning, (d) causal potential theory and its enhanced rho-diagram equations for DAG causal analyses.

 

Biography: Lei Xu, Emeritus Professor, Chinese University of Hong Kong; Zhiyuan Chair Professor, Shanghai Jiao Tong University (SJTU); Chief Scientist of SJTU AI Research Institute, and of SJTU-Sensetime Research Institute; Director of Neural Computation Research Centre in Brain and Intelligence Science-Technology Institute, ZhangJiang National Lab; Received several national and international academic awards, including 1993 National Nature Science Award, 1995 Leadership Award from International Neural Networks Society (INNS) and 2006 APNNA Outstanding Achievement Award. Elected to Fellow of IEEE in 2001; Fellow of intl. Association for Pattern Recognition in 2002 and of European Academy of Sciences (EURASC) in 2003. Published about 100 Journal papers, given over dozens keynote /invited lectures at various international conferences. Served as EIC and associate editors of several academic journals, e.g., including Neural Networks (1995-2016), IEEE Tr. Neural Networks (1994-98). Taken various roles in academic societies, e.g., INNS Governing Board (2001-03), the INNS award committee (2002-03), and the Fellow committee of IEEE Computational Intelligence society (2006-07), and the EURASC scientific committee (2014-17).


   

Keynote Speaker 3:

Prof. Shyi-Ming Chen,

Fellow of IEEE, IET Fellow, IFSA Fellow, National Taiwan University of Science and Technology, Taiwan

 

Speech Title: Fuzzy Forecasting Based on Two-Factors High-Order Fuzzy Time Series

 

Abstract: In our daily life, we often use forecasting techniques to predict the weather, the earthquakes, the stock index, the temperature, etc. Traditional forecasting methods cannot deal with forecasting problems whose historical data are linguistic values. In recent years, some researchers used fuzzy time series to handle forecasting problems. In this talk, we introduce a fuzzy forecasting method based on two factors high-order fuzzy time series to forecast the temperature and the TAIFEX (Taiwan Futures Exchange). We also offer some research directions, which are worth pursuing for future research.

 

Biography: Professor Shyi-Ming Chen received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. He is a Chair Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. From August 2007 to July 2010, he was the Dean of the College of Electrical Engineering and Computer Science, Jinwen University of Science and Technology, New Taipei City, Taiwan. From August 2011 to July 2012, he was the Vice President of the National Taichung University of Education, Taichung, Taiwan. He was the President of the Taiwanese Association for Artificial Intelligence (TAAI) from January 2005 to January 2009. He was the President of the Taiwanese Association for Consumer Electronics (TACE) from December 2008 to December 2012 and from December 2014 to December 2016. He has published more than 520 papers in referred journals, conference proceedings and book chapters. His research interests include Fuzzy Systems, Intelligent Systems, Knowledge-Based Systems, Neural Networks, Data Mining, Information Retrieval, and Genetic Algorithms.

 

Professor Chen is an IEEE Fellow, an IET Fellow and an IFSA Fellow. He was a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics (SMC) Society from 2012 to 2015. He has received numerous honors and awards, including the 2001 Distinguished Talented Person Award, Republic of China, for Distinguished Contributions in Information Technologies, the 2002 Distinguished Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE), Republic of China, and the 2008 Distinguished Engineering Professor Award granted by the Chinese Institute of Engineers (CIE), Republic of China. He was a 2014 Fellow Evaluation Committee Member of the IEEE Systems, Man, and Cybernetics Society.

 

Professor Chen is an Editor-in-Chief of Granular Computing, an Associate Editor-in-Chief of Applied Intelligence, an Associate Editor of IEEE Transactions on Fuzzy Systems, an Associate Editor of the IEEE Transactions on Cybernetics, an Associate Editor of Information Sciences, an Editorial Board Member of Information Fusion, an Editorial Board Member of Applied Soft Computing, an Editorial Board Member of Applied Intelligence, an Associate Editor of the Journal of Intelligent & Fuzzy Systems, an Associate Editor of the International Journal on Artificial Intelligence Tools, an Associate Editor of the International Journal of Pattern Recognition and Artificial Intelligence, an Editor of New Mathematics and Natural Computation, an Associate Editor of the International Journal of Fuzzy Systems, an Associate Editor of the Journal of Information Science and Engineering, an Associate Editor of Fuzzy Optimization and Decision Making, an Editorial Board Member of Knowledge-Based Systems, and an Associate Editor of the International Journal of Innovative Computing, Information and Control. He was an Associate Editor of the IEEE Transactions on Fuzzy Systems, an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, an Associate Editor of the IEEE Computational Intelligence Magazine, and an Editorial Board Member of Soft Computing.

   

Plenary Speaker 1:

Prof. Lars Lundberg
Blekinge Institute of Technology, Sweden

 

Biography: Lars Lundberg is since 20 years a full professor of computer systems engineering at Blekinge Institute of Technology (BTH) in Sweden. Lars took has a master in computer science from Linköping university (Sweden), and a Ph.D. from Lund University (Sweden). Professor Lundberg has had a number of tasks at BTH, including being the dean of the technical faculty for six years, and the head of the department of computer science and engineering. Currently he is the dean of the faculty of computing at Blekinge Institute of Technology. Professor Lundberg has a long track record of working with industry in Sweden, USA, India and China. Lars has advised 14 PhD students to their doctoral degree and published more than 200 papers in international journals and conferences. His research interests include machine learning, real-time systems, high-performance processing, software engineering and cloud computing.

 

 

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