activity
20182020
most citedAdaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs

6 citations · 6 across the 1 of their papers we have counts for

collaborators

5 papers

cs.SI2020

The Impact of COVID-19 on Flight Networks

Toyotaro Suzumura, Hiroki Kanezashi, Mishal Dholakia +5

As COVID-19 transmissions spread worldwide, governments have announced and enforced travel restrictions to prevent further infections. Such restrictions have a direct effect on the…

cs.LG2019

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Aldo Pareja, Giacomo Domeniconi, Jie Chen +6

Graph representation learning resurges as a trending research subject owing to the widespread use of deep learning for Euclidean data, which inspire various creative designs of neu…

cs.DB20186 cited

Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs

Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla +2

Graph pattern matching algorithms to handle million-scale dynamic graphs are widely used in many applications such as social network analytics and suspicious transaction detections…

cs.SI2018

Scalable Graph Learning for Anti-Money Laundering: A First Look

Mark Weber, Jie Chen, Toyotaro Suzumura +6

Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels have murdered 150,000 people since 2006, upwards of 700,000 people per year are "exported" i…

cs.DB2018

System G Distributed Graph Database

Gabriel Tanase, Toyotaro Suzumura, Jinho Lee +5

Motivated by the need to extract knowledge and value from interconnected data, graph analytics on big data is a very active area of research in both industry and academia. To suppo…