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自动化学术论坛[2023第97-102期]:加拿大阿尔伯塔大学Witold Pedrycz教授学术报告会

复杂系统先进控制与智能自动化秋季国际研讨会系列报告之(二十四 ~ 二十九


报告形式教学综合楼B0506ZOOM

人:Witold Pedrycz,加拿大阿尔伯塔大学教授

      University of AlbertaCanada

报告主题Intelligent systems and Computing


(一

报告时间20231113日(星期10:05 11:40

报告地点教学综合楼B0506

主要内容. Machine Learning, Information Granules, and Granular Computing

Introductory notes, motivation

Fundamental performance measures of constructs of Machine Learning

Key challenges of Machine Learning

Information granules – formal representation environments

Interval calculus

Fuzzy sets

Operations on information granules

报告时间20231115日(星期10:05 11:40

报告地点教学综合楼B0506

主要内容. Granular Computing: knowledge acquisition problems

Method of pairwise comparison

Clustering methods: taxonomy, example algorithms, interpretation of results,

Comparative analyses

Principle of justifiable granularity and classification architectures

报告时间20231130日(星期10:05 11:40

报告地点教学综合楼B0506ZOOMID980 7954 9546Passcode: 422471

主要内容. Interpretable and Explainable Machine Learning

Basic notions

Local interpretable models -agnostic exploration (LIME)

Counterfactual explanation

Brittleness of Machine Learning models

Feature importance- assessment methods

报告时间20231218日(星期10:05 11:40

报告地点教学综合楼B0506ZOOMID992 2067 8023Passcode: 791111

主要内容. Rule-based computing

Functional rules and mixture of experts: analysis and basic design

Quality of rules for prediction and classification

Rule-based classifiers

Fuzzy neurocomputing

报告时间202414日(星期10:05 11:40

报告地点教学综合楼B0506ZOOMID982 2025 1478Passcode: 266427

主要内容. Credibility of Machine Learning models

Motivating arguments

Confidence and prediction information granules and main relationships

Gaussian process model

Granular embedding

报告时间202418日(星期10:05 11:40

报告地点教学综合楼B0506ZOOMID947 7441 8569Passcode: 803376

主要内容. Federated Learning, Transfer Learning, and knowledge distillation

Algorithms of federated learning- main ideas and design schemes (averaged and gradient based federated learning)

Transfer learning – towards sustainable learning

Knowledge distillation- learning schemes for classification and regression

报告人简介: 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 numerous papers in these areas; the current h-index is 114 (Google Scholar) and 87 on the list top-h scientists for computer science and electronics http://www.guide2research.com/scientists/. 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.