中文版：
题目：流数据挖掘：从窗口滑动到深度学习
报告人：Leszek Rutkowski 院士
工作单位：罗兹社会科学大学（波兰）
报告题目：流数据挖掘：从窗口滑动到深度学习
报告时间：2022年9月13日（周二）15:00-16:00
报告链接：https://meeting.tencent.com/dm/CP6CO9nXtkw8 （腾讯会议）
（会议号：508 867 673）
内容摘要：
本报告将介绍流数据挖掘的原始方法和算法的集合。与之前绝大多数基于启发式的方法不同，流数据挖掘突出了方法和算法在数学上的合理性。首先，本报告将概述流数据挖掘的基本概念，并特别强调概念漂移——描述流数据随时间变化的特性。接下来，将描述如何调整静态决策树以适应数据流；在这方面，提出新的分裂准则，以保证它们与经典的批处理树渐近等价。此外，还设计了新的决策树，形成杂交树的原始概念。随后，将采用基于 Parzen 核的非参数技术以及正交序列来解决时变环境中非平稳回归和分类问题中的概念漂移问题。下一步将描述并解决一个极具挑战性的问题，该问题包括设计集成和自动选择它们的大小。最后，将展示如何使用受限玻尔兹曼机进行流数据处理和监控。
个人简介：
Leszek Rutkowski 院士（IEEE Fellow）分别于1977年、1980年和1986年在波兰弗罗茨瓦夫理工大学获得理学硕士学位、博士学位和科学博士学位，并于2014年在波兰克拉科夫 AGH 科技大学获得荣誉学位。Leszek Rutkowski 院士目前担任琴斯托霍瓦大学的名誉教授，波兰罗兹社会科学大学信息技术研究所教授，《Journal of Artificial Intelligence and Soft Computing Research》主编以及《IEEE Transactions on Cybernetics》、《International Journal of Neural Systems》、《International Journal of Applied Mathematics and Computer Science》、《International Journal of Biometric, Knowledge and Information Systems》的编委，并与波兰华沙的波兰科学院系统研究所和波兰克拉科夫 AGH 科技大学计算机科学研究所在人工智能和软计算领域开展合作。Leszek Rutkowski 院士研究方向包括：数据流挖掘、大数据分析、神经网络、代理系统、模糊系统、图像处理、模式分类和专家系统，目前已发表300余篇学术论文，并出版专著：《Computational Intelligence》 (斯普林格, 2008年, 波兰语和俄语版), 《New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing》 (斯普林格, 2004年),《 Flexible Neuro-Fuzzy Systems》 (Kluwer Academic，2004年），《Methods and Techniques of Artificial Intelligence》（2005年，波兰语），《Adaptive Filters and Adaptive Signal Processing》（1994年，波兰语），并合著了《Neural Networks, Genetic Algorithms and Fuzzy Systems》（1997年）以及《Neural Networks for Image Compression 》（2000年）。Leszek Rutkowski 院士是波兰神经网络协会主席和创始人，曾担任 1996 年、1997 年、1999 年、2000 年、2002 年、2004 年、2006 年、2008 年、2010 年以及 2012-2022 年每年举办的人工智能和软计算国际会议总主席，《IEEE Transactions on Neural Networks》(1998-2005年) 和《IEEE Systems Journal》(2007-2010年)、《Evolving Systems》(2017-2019年) 等期刊副主编。Leszek Rutkowski 院士曾获《IEEE Transactions on Neural Networks》（2005）杰出论文奖，并在 IEEE 计算智能协会担任杰出讲师计划主席（2008-2009）和标准委员会主席（2006-2007）。Leszek Rutkowski 院士于2016年当选波兰科学院院士，于2022年当选欧洲科学院院士，是 IEEE 计算智能协会波兰分会的创始主席，该协会曾获 2008 年杰出分会奖。
【编辑：王健】
英文版：
题目：Academic Report Notice of Leszek Rutkowski：Stream Data Mining: From Sliding Windows to Deep Learning
Speaker: Professor Leszek Rutkowski
Title: Stream Data Mining: From Sliding Windows to Deep Learning
Time: 15:00-16:00, September 13, 2022 (Tuesday)
Website: https://meeting.tencent.com/dm/CP6CO9nXtkw8 (Tencent Conference)
(meeting number:508 867 673）
Abstract:
This lecture presents a collection of original methods and algorithms for stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, the basic concepts of stream data mining are outlined with a special emphasis put on concept drift – the phenomenon describing the time-varying nature of streaming data. Next, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Next, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Finally, it will be shown how to use Restricted Boltzmann Machines for stream data processing and monitoring.
Personal Introduction:
Leszek Rutkowski received the M.Sc. , Ph.D. and D.Sc. degrees from the Wrocław University of Technology, Wrocław, Poland, in 1977, 1980 and 1986, respectively, and the Honoris Causa degree from the AGH University of Science and Technology, Kraków, Poland, in 2014. He is a Honorary Professor of Czestochowa University of Technology, Poland, and serves as a Full Professor in the Institute of Information Technology at the University of Social Sciences, Łódź, Poland. He is also cooperating with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland, and with the Institute of Computer Science, AGH University of Science and Technology, Krakow, Poland, in the area of artificial intelligence and soft computing. From 1987 to 1990, he held a visiting position with the School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA. His research interests include data stream mining, big data analysis, neural networks, agent systems, fuzzy systems, image processing, pattern classification, and expert systems. He has published more than 300 technical papers, including more than 30 in various series of IEEE Transactions. He is the author of the following books: Computational Intelligence (Springer, 2008, available also in Polish and Russian), New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Springer, 2004), Flexible Neuro-Fuzzy Systems (Kluwer Academic, 2004), Methods and Techniques of Artificial Intelligence (2005, in Polish), Adaptive Filters and Adaptive Signal Processing (1994, in Polish), and co-author of two others in Polish: Neural Networks, Genetic Algorithms and Fuzzy Systems (1997) and Neural Networks for Image Compression (2000). His recent monograph on stream data mining has been published by Springer in the series Studies in Big Data. He is the president and founder of the Polish Neural Networks Society. He organized and served as a General Chair of the International Conferences on Artificial Intelligence and Soft Computing held in 1996, 1997, 1999, 2000, 2002, 2004, 2006, 2008, 2010, and annulally in 2012 -2022. He was an associate editor of the IEEE Transactions on Neural Networks (1998-2005) and IEEE Systems Journal (2007-2010), Evolving Systems (2017-2019) and few others. He is an editor-in-chief of the Journal of Artificial Intelligence and Soft Computing Research, and he is on the editorial board of the IEEE Transactions on Cybernetics, International Journal of Neural Systems, International Journal of Applied Mathematics and Computer Science , International Journal of Biometric, Knowledge and Information Systems. He is a recipient of the IEEE Transactions on Neural Networks 2005 Outstanding Paper Award. He served in the IEEE Computational Intelligence Society as the chair of the Distinguished Lecturer Program (2008-2009) and the chair of the Standards Committee (2006-2007). He is the founding chair of the Polish chapter of the IEEE Computational Intelligence Society, which won the 2008 Outstanding Chapter Award. In 2004, he was awarded by the IEEE Fellow membership grade for contributions to neurocomputing and flexible fuzzy systems. He received a degree honoris causa from the prestigious AGH University of Science and Technology in Cracow “in recognition of outstanding scientific achievements in the field of artificial intelligence - in particular, neuro-fuzzy systems”. He is a Full Member of the Polish Academy of Sciences, lected in 2016, and Member of Academia of Europea, elected in 2022.
[Editor: Jian Wang]