Heterogeneous Graph Representation Learning and Applications
Chuan Shi, Philip S. Yu, Xiao Wang
Sold by Buchpark, Trebbin, Germany
AbeBooks Seller since 30 September 2021
Used - Soft cover
Condition: Hervorragend
Quantity: 1 available
Add to basketSold by Buchpark, Trebbin, Germany
AbeBooks Seller since 30 September 2021
Condition: Hervorragend
Quantity: 1 available
Add to basketZustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
Seller Inventory # 41378366/1
Xiao Wang is the assistant professor in School of Computer Sciences of Beijing University of Posts and Telecommunications. He was a postdoc in the Department of Computer Science and Technology at Tsinghua University. He got his Ph.D. in the School of Computer Science and Technology at Tianjin University and a joint-training Ph.D. at Washington University in St. Louis. The main research interests include data mining, machine learning, artificial intelligence and big data analysis. He has published more than 50 refereed papers, including top journals and conferences in data mining, such as IEEE TKDE, KDD, AAAI, IJCAI, and WWW. He also serves as SPC/PC member and Reviewer of several high-level international conferences, e.g., KDD, AAAI, IJCAI, and journals, e.g., IEEE TKDE.
Philip S. Yu's main research interests include big data, data mining (especially on graph/network mining), social network, privacy preserving data publishing, data stream, database systems, and Internet applications and technologies. He is a Distinguished Professor in the Departmentof Computer Science at UIC and also holds the Wexler Chair in Information and Technology. Before joining UIC, he was with IBM Thomas J. Watson Research Center, where he was manager of the Software Tools and Techniques department. Dr. Yu has published more than 1,300 papers in refereed journals and conferences with more than 133,000 citations and an H-index of 169. He holds or has applied for more than 300 US patents. Dr. Yu is a Fellow of the ACM and the IEEE. He is the recepient of ACM SIGKDD 2016 Innovation Award and the IEEE Computer Society's 2013 Technical Achievement Award.
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