前沿论坛

报告题目：Graph machine learning

报告人：Prof. Ilya Makarov (HSE University)

报告时间：2022年4月27日下午3:00~4:30

报告地点：Zoom会议（会议号：961 7256 9989  密码：123456）

报告内容简介：Many systems in the real world can be modeled as graphs or networks. One of the main goals of graph modeling is to formulate a general technique able to process structural data including relations between objects, which may also have some domain-specific information. In this talk, we deal with network representation learning, aiming to automatically learn low-dimensional vector features for the simplest graph motifs, such as nodes and edges. We search for a way that would efficiently solve machine learning problems on graphs, which include node classification, link prediction, node clustering, and graph visualization. Reference: https://peerj.com/articles/cs-357/

报告人简介：Ilya Makarov（伊利亚·马卡罗夫），1989年7月，俄罗斯国立高等经济大学（HSE University），数据分析与人工智能学院，高级讲师；人工智能研究所，高级研究员。作为人工智能教育者、HSE研究员、MIPT（莫斯科物理技术学院）研究员、MISIS（密西斯大学）研究员以及莫斯科三星和华为研发部门的顾问工作了近10年。