题目一：Attributed Network Learning: Data and Algorithms
内容简介：In many networked systems, nodes are associated with a rich set of data describing their characteristics, which can be modeled as attributed networks. To perform attributed network learning, Graph neural networks (GNNs) have been intensively studied. In this talk, from the algorithm aspect, I will introduce the latest GNN architectures we are exploring, i.e., Cross-Correlated GNNs. Then, from the data aspect, I will discuss the opportunities that large language models can bring to attributed network learning.
报告人：Xiao Huang (黄啸)
报告人简介：Xiao Huang is an assistant professor in the Department of Computing at The Hong Kong Polytechnic University. He received Ph.D. in Computer Engineering from Texas A&M University in 2020, and B.S. in Engineering from Shanghai Jiao Tong University in 2012. His research interests include data mining and information retrieval. His publications are well recognized by the community and have received over 2200 citations. He is a program committee member of NeurIPS 2021-2023, AAAI 2021-2023, ICLR 2022-2023, KDD 2019-2023, TheWebConf 2022-2023, ICML 2021-2023, IJCAI 2020-2023, CIKM 2019-2022, WSDM 2021-2023. Before joining PolyU, he worked as a research intern at Microsoft Research and Baidu USA.
题目二：Recommendation---Algorithms, Applications and Realistic
内容简介：Recommendation systems stand as the most impactful deep learning applications in our day-to-day lives. Moreover, the role of recommendation algorithm developers has proven to be one of the most rewarding positions in internet-based enterprises. In today's presentation, we are privileged to have Dr. Chen, an experienced professional with three years' tenure in the foundational team of WeChat Channels. Dr. Chen will deliver an in-depth and comprehensive discussion on the algorithms, their applications, and the real-world operational status of recommendation systems.
报告人：Hao Chen (陈昊)
报告人简介：Hao Chen is a postdoc fellow in the Department of Computing at The Hong Kong Polytechnic University. He received Ph.D. in Computer Engineering from Beihang University in 2022, and B.S. of Science from Nankai University in 2015. His research interests include large language models and information retrieval. Before joining PolyU, he worked as a senior algorithm developer in WeChat Channels.
时 间：2023年6月20日（周二）下午 14：30 始
地 点：番禺校区知识产权大楼东区6层会议室
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2023年6月19日
