2019年11月22日，新加坡南洋理工大学P.N.Suganthan教授和西安电子科技大学公茂果为IEEE郑州大学学生分会和郑州大学计算智能实验室成员作学术报告并进行学术交流。
报告题目：Randomization-Based Deep and Shallow Neural Networks
报告人：P. N Suganthan 教授
报告时间：2019年11月22日（星期五）下午14:00-15:30
报告地点：电气工程学院二楼大会议室
报告介绍：
This talk will first introduce the main randomization-based feedforward neural networks with closed-form solutions. The popular instantiation of the feedforward type called random vector functional link neural network （RVFL） originated in early 1990s. RVFL variants will be empirically evaluated. Subsequently, deep versions of RVFL will be presented as a single and ensemble classifiers. The talk will also present extensive benchmarking studies using classification and forecasting datasets.
报告人简介：
Ponnuthurai Nagaratnam Suganthan received the B.A degree, Postgraduate Certificate and M.A degree in Electrical and Information Engineering from the University of Cambridge, UK in 1990, 1992 and 1994, respectively. After completing his PhD research in 1995, he served as a pre-doctoral Research Assistant in the Dept. of Electrical Engineering, University of Sydney in 1995–96 and a lecturer in the Dept. of Computer Science and Electrical Engineering, University of Queensland in 1996–99. He moved to Singapore in 1999. He is a founding co-editor-in-chief of Swarm and Evolutionary Computation （2010 - ）, an SCI Indexed Elsevier Journal with an impact factor of 6.33 in 2019-2020. He is an associate editor of Applied Soft Computing （Elsevier, 2018-）, Neurocomputing （Elsevier, 2018-）, IEEE Trans on Evolutionary Computation （2005 -）, Information Sciences （Elsevier, 2009 - ）, Pattern Recognition （Elsevier, 2001 - ） and Int. J. of Swarm Intelligence Research （2009 - ） Journals. He was an Editorial Board Member of theEvolutionary Computation Journal, MIT Press （2013-2018） and an associate editor of the IEEE Trans on Cybernetics （2012 - 2018）. His co-authored SaDE paper （published in April 2009） won the ”IEEE Trans. on Evolutionary Computation outstanding paper award” in 2012. His former PhD student, Dr Jane Jing Liang, won the IEEE CIS Outstanding PhD dissertation award, in 2014. His research interests include swarm and evolutionary algorithms, pattern recognition, forecasting, randomized neural networks, deep learning and applications of swarm, evolutionary & machine learning algorithms. His SCI indexed publications attracted over 1000 SCI citations in a calendar year since 2013. He was selecｔed as one of the highly cited researchers by Thomson Reuters every year from 2015 to 2019 in computer science. He served as the General Chair of the IEEE SSCI 2013. He is an IEEE CIS distinguished lecturer （DLP） in 2018-2020. He has been a member of the IEEE （Sˊ91, Mˊ92, SMˊ00, Fellow’15） since 1991 and an elected AdCom member of the IEEE Computational Intelligence Society （CIS） in 2014-2016.
报告题目：用演化计算求解深度神经网络基础难题的探索
报告人：公茂果 教授
报告时间：2019年11月22日（星期五）下午15:30-17:00
报告地点：电气工程学院二楼大会议室
报告介绍：
面对大数据的诸多挑战，深度神经网络借助其深层结构，具备很强的复杂问题建模能力，在计算机视觉、人机对弈等很多应用中取得了突破性的进展。然而，深度神经网络在理论研究上仍然存在亟待解决的瓶颈难题。首先深度网络的结构设计困难，如网络层数、节点数目等都需要人工设定；同时，模型的表达参数对性能的影响显著，需要反复调参；而且，基于梯度的网络优化方法存在梯度弥散和陷入局部最优的缺点。本报告将介绍利用演化多目标优化解决上述难题的一些尝试，并汇报在深度神经网络解决空时影像变化检测关键难题上的一些最新进展。
报告人简介：
公茂果，教授，博士生导师，西安电子科技大学计算智能研究所所长，陕西省重点科技创新团队负责人，国家重点研发计划项目负责人 ，国家“万人计划”领军人才。主要研究方向为计算智能理论与应用。主持完成十余项国家课题，发表SCI检索论文100余篇，被引用9000余次，入选中国高被引学者，授权国家发明专利30余项，获2013年国家自然科学奖二等奖和2016年教育部自然科学奖二等奖。担任IEEE演化计算汇刊、IEEE神经网络与学习系统汇刊等期刊编委，中国人工智能学会理事等。
Suganthan教授为电气学院师生作学术报告
公茂果教授为电气学院师生作学术报告
Suganthan教授、公茂果教授与电气学院师生合影
