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主讲人：Lorna Uden地点：一号学院楼140室时间：2018年11月13日（周二）上午10:05组织单位：太阳集团tcy8722报告人简介(Reporter introduction)：Prof. Lorna Uden is Emeritus Professor of IT systems in the school of Computing, Engineering and Technology at Staffordshire University. She has published widely in conferences, journals, chapters of books and workshops. Her research interests inc...
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主题: Select representative data to train SVM for big data classification主讲人: Xiaoou Li 地点: 松江校区一号学院楼140报告厅时间: 2018-11-15 13:00:00组织单位: 我院主讲人简介：Prof. Xiaoou Li obtained B. S degree of appliedmathematics in 1991 and PhD degree of Automatic Control in 1995 fromNortheastern University, S...
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主题: Building Risk Scores for Evaluating Survival after Hematopoietic Cell Transplantation Using Pre-Tran主讲人: Lue Ping Zhao 地点: 松江校区一号学院楼140报告厅时间: 2018-10-23 13:00:00组织单位: 我院主讲人简介：Dr. Lue Ping Zhao has received his trainingfrom Biostatistics, Computer Science, and Public Health Scien...
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主题: Industrial IoT plus AI.主讲人: Tingting Zhang 地点: 松江校区一号学院楼140报告厅时间: 2018-10-25 13:30:00组织单位: 我院主讲人简介：Tingting Zhang is professor in computerengineering, researchleader for computerscience and engineeringresearch in Mid SwedenUniversity and wireless sensornetwork and security(SNS) ...
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讲座摘要: Graph has been widely adopted to model complex networks. Finding hidden structures in massive graphs is an important issue.For online social networks, there are two interesting issues: social hierarchy and social communities.Social hierarchy is a fundamental concept in sociology and social network analysis. The importance of social hierarchy in a social network is that the top...
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主讲人简介：Monson Hayes is Professor and Chair of the Department of Electrical and Computer Engineering at George Mason University in Fairfax, Virginia. Dr. Hayes was a Professor of Electrical and Computer Engineering at the Georgia Institute of Technology (1981-2011), and served as an Associate Chair in the School of ECE at Georgia Tech, and as Associate Director for Georgia Tech Savannah. Dr. H...
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摘要:The presentation will focus on 'what should be avoided when working in data science'. Instead of describing more concrete state-of-art methodology and techniques related to advanced data analytics, the topic will mainly cover the easily missed-out things/blind points when working in data science area. All the arguments will be discussed with the combination of with work...
