Report title: Efficient Approximate Computation of Large Graph Data
Reporting location: offline Computer Building, Central South University Headquarters313
Report time: 2023YearFebruary 23日 10:00-11:30
Reporter information:
Ma Shuai,Double PhD (Peking University '2004，University of Edinburgh'2011)，Beijing University of Aeronautics and Astronautics School of Computer Science (first batch) tenured professor、Doctoral Supervisor，Director of the International Research Center for “Big seabet sports betting Data Science and Engineering”，Member of the expert group of the Military Science and Technology Commission 163-15-02 project，Standing Committee Member of CCF Database Professional Committee、Member of Big Data Expert Committee。Main research direction is big data、Database theory and system, etc.。Research work continues to be published in the database、Data Mining、Artificial Intelligence、Top international journals and conferences such as Computer Theory and Systems，Published more than 100 high-level papers。VLDB seabet app download Journal (2017~2020), the top journal in the database field、Editorial board member of IEEE Transaction On Big Data (2020~) and Knowledge and Information Systems (KAIS), a well-known journal in the field of big data。Won the only best paper award in VLDB, the top international conference in the database field, in 2010、Won the Science and Technology Special Award of the Institute of Electronics in 2017、Won the National Science Foundation for Distinguished Young Scholars (National Distinguished Young Scholars) in 2019、2019 ICDM Candidate seabet online sports betting Best Paper、Won the distinguished speaker of the internationally renowned conference ICA3PP in 2021。
Report Summary:
Strong ability to express graph data，Becoming one of the key concerns of industry and academia。This report will introduce a main method for efficient large graph data calculation，Approximate calculation (including query approximation and data approximation)，Introduce the ideas of related methods through cases。Last，Discuss potential research directions in approximate computing。
