On Optimal Transport-based Statistical Measures for Graph Structured Data and Applications

Research Project

Project/Area Number	23K16939
Research Category	Grant-in-Aid for Early-Career Scientists
Allocation Type	Multi-year Fund
Review Section	Basic Section 61030:Intelligent informatics-related
Research Institution	University of Tsukuba
Principal Investigator	NGUYEN DAIHAI 筑波大学, システム情報系, 助教 (50968401)
Project Period (FY)	2023-04-01 – 2026-03-31
Project Status	Granted (Fiscal Year 2023)
Budget Amount *help	¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000) Fiscal Year 2025: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000) Fiscal Year 2024: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000) Fiscal Year 2023: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords	graph kernels / optimal transport / graph structured data
Outline of Research at the Start	We design novel measures for graphs with the following advantages: 1) taking into account node features and global structures of graphs. 2) deriving valid kernels that can be used for kernel-based frameworks. 3) reducing the complexity of computing the pairwise distance or kernel matrices.