浙江11选5体彩 www.vbeui.com Graph Kernels and Embeddings: A Brief Overview
主 講 人 ：Manohar Kaul Assistant Professor
地 點 ：理科群1號樓D-203室
Graph representation learning is an important taskwith several applications in different domains. The challenge in this domain isto find a way to encode a graph structure so that it can be easily exploited bymachine learning models. Traditional machine learning approaches used userdefined methods to extract graph properties, whereas recent methodsautomatically learn graph structural properties as embeddings. The talk willcover variants of graph kernels and graph embedding methods along with theapplications (node classification and link prediction).
Dr. Manohar Kaul is an Assistant Professor in theDepartment of Computer Science and Engineering at the Indian Institute ofTechnology Hyderabad, India.（印度海得拉巴理工學院） He won the Outstanding Academic Achievement Award from AustralianComputer Society in 2000. His research paper "Building Accurate 3D SpatialNetworks to Enable Next Generation Intelligent Transportation Systems",won the Best Paper Award of Mobile Data Management in 2013. In 2017—2018, hevisited Institute of Statistical Mathematics and Shinshu University, Japan. Hehas published conference papers in top-tier venues of databases and machinelearning. His research interests include Machine Learning, Applied AlgebraicTopology, and Spatial / Spatio-Temporal Databases.