学　术

　　人力资源部教师发展中心“名师讲堂”活动特别邀请到华南理工大学陈俊龙教授做线上学术交流。具体安排如下，欢迎广大师生参加。

　　一、主　题：动态结构神经网络及其在开放环境下的应用

　　二、主讲人：华南理工大学　陈俊龙　教授

　　三、时　间：2021年12月9日（周四）9:30-11:00

　　四、参会方式：腾讯会议　会议 ID：827 754 807

　　五、主讲内容：

　　Learning in neural networks suffers from the fixed structure of the network with a given number of layers and neurons when gather information for training. When the learning is unsatisfied, a new structure is re-designed and the process is repeated. In this talk, a dynamic neural network structure via Stacked Broad Learning Systems (BLS) will be discussed. The BLS has been proved to be effective and efficient lately. The proposed dynamic model is a novel incremental stacking of BLS. This invariant inherits the efficiency and effectiveness of BLS that the structure and weights of lower layers of BLS are fixed when the new blocks are added. The modified incremental stacking algorithm only computes the connection weights within the BLS block while the connecting weights of the lower stacks remains fixed, making the learning process very efficient. Experimental results on UCI datasets, MNIST dataset, NORB dataset, CIFAR-10 dataset, SVHN dataset, and CIFAR-100 dataset indicate that the proposed method outperforms the other state-of-the-art methods on both accuracy and training speed, such as Deep Residual Networks.In addition, taking the advantages of BLS that can accumulate and reuse the learned knowledge, applications of BLS, Federated Broad Learning, in an open environment will be discussed.

　　六、嘉宾简介：

       C. L. Philip Chen  is the Chair Professor and Dean of the College of Computer Science and Engineering, South China University of Technology and was a Chair Professor of the Faculty of Science and Technology, University of Macau, where he was the former Dean (2010-2017), after he left a professorship position in the USA for 23 years. He is a Fellow of IEEE, AAAS, IAPR, CAA, and HKIE. He received IEEE Norbert Wiener Award in 2018 for his contribution in systems and cybernetics, and machine learnings; and IEEE Joseph G. Wohl Career Award for his contributions in SMCS and IEEE in 2021. He was a recipient of the 2016 Outstanding Electrical and Computer Engineers Award from his alma mater, Purdue University. He received IEEE Transactions on Neural Networks and Learning Systems best transactions paper award two times for his papers in 2014 and 2018. He is a highly cited researcher by Clarivate Analytics from 2018 to 2021 continuously.

        Currently, he is the Editor-in-Chief of the IEEE Transactions on Cybernetics. He was the Editor-in-Chief of the IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014-2019). the IEEE Systems, Man, and Cybernetics Society President from 2012 to 2013, an Associate Editor of the IEEE Transactions on AI, IEEE Trans on SMC: Systems, and IEEE Transactions on Fuzzy Systems, an Associate Editor of China Sciences: Information Sciences. He received Macau FDCT Natural Science Award three times and a First-rank Guangdong Province Scientific and Technology Advancement Award in 2019. His current research interests include cybernetics, computational intelligence, and systems.

　　七、主办单位：人力资源部教师发展中心

　　　　承办单位：自动化工程学院

　　　　　　　　　　　　　　　　　　　　　　　　　　人力资源部教师发展中心

　　　　　　　　　　　　　　　　　　　　　　　　　　　　2021年12月6日