Toyotaro Suzumura

Efficient Scaling of Dynamic Graph Neural Networks

We present distributed algorithms for training dynamic Graph Neural Netw...
09/16/2021 ∙ by Venkatesan T. Chakaravarthy, et al. ∙ 50 ∙ share

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Finding All Bounded-Length Simple Cycles in a Directed Graph

A new efficient algorithm is presented for finding all simple cycles tha...
05/21/2021 ∙ by Anshul Gupta, et al. ∙ 0 ∙ share

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Heterogeneous Graph Neural Networks for Multi-label Text Classification

Multi-label text classification (MLTC) is an attractive and challenging ...
03/26/2021 ∙ by Irene Li, et al. ∙ 0 ∙ share

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Time-Efficient and High-Quality Graph Partitioning for Graph Dynamic Scaling

The dynamic scaling of distributed computations plays an important role ...
01/18/2021 ∙ by Masatoshi Hanai, et al. ∙ 0 ∙ share

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The Impact of COVID-19 on Flight Networks

As COVID-19 transmissions spread worldwide, governments have announced a...
06/04/2020 ∙ by Toyotaro Suzumura, et al. ∙ 0 ∙ share

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Benchmarking Graph Data Management and Processing Systems: A Survey

The development of scalable, representative, and widely adopted benchmar...
05/26/2020 ∙ by Miyuru Dayarathna, et al. ∙ 0 ∙ share

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Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincaré Embeddings

In the recent years money laundering schemes have grown in complexity an...
12/04/2019 ∙ by Lucia Larise Stavarache, et al. ∙ 0 ∙ share

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Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis

Recently, there has been a surge of interest in the use of machine learn...
09/24/2019 ∙ by Daiki Matsunaga, et al. ∙ 0 ∙ share

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Towards Federated Graph Learning for Collaborative Financial Crimes Detection

Financial crime is a large and growing problem, in some way touching alm...
09/19/2019 ∙ by Toyotaro Suzumura, et al. ∙ 0 ∙ share

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Distributed Edge Partitioning for Trillion-edge Graphs

We propose Distributed Neighbor Expansion (Distributed NE), a parallel a...
08/16/2019 ∙ by Masatoshi Hanai, et al. ∙ 0 ∙ share

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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Graph representation learning resurges as a trending research subject ow...
02/26/2019 ∙ by Aldo Pareja, et al. ∙ 20 ∙ share

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Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs

Graph pattern matching algorithms to handle million-scale dynamic graphs...
12/21/2018 ∙ by Hiroki Kanezashi, et al. ∙ 0 ∙ share

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

Organized crime inflicts human suffering on a genocidal scale: the Mexic...
11/30/2018 ∙ by Mark Weber, et al. ∙ 0 ∙ share

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An incremental local-first community detection method for dynamic graphs

Community detections for large-scale real world networks have been more ...
08/19/2018 ∙ by Hiroki Kanezashi, et al. ∙ 0 ∙ share

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Scalable attribute-aware network embedding with locality

Adding attributes for nodes to network embedding helps to improve the ab...
04/17/2018 ∙ by Weiyi Liu, et al. ∙ 0 ∙ share

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Scalable attribute-aware network embedding with localily

Adding attributes for nodes to network embedding helps to improve the ab...
04/17/2018 ∙ by Weiyi Liu, et al. ∙ 0 ∙ share

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System G Distributed Graph Database

Motivated by the need to extract knowledge and value from interconnected...
02/08/2018 ∙ by Gabriel Tanase, et al. ∙ 0 ∙ share

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Full-Network Embedding in a Multimodal Embedding Pipeline

The current state-of-the-art for image annotation and image retrieval ta...
07/24/2017 ∙ by Armand Vilalta, et al. ∙ 0 ∙ share

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Building Graph Representations of Deep Vector Embeddings

Patterns stored within pre-trained deep neural networks compose large an...
07/24/2017 ∙ by Dario Garcia-Gasulla, et al. ∙ 0 ∙ share

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Can GAN Learn Topological Features of a Graph?

This paper is first-line research expanding GANs into graph topology ana...
07/19/2017 ∙ by Weiyi Liu, et al. ∙ 0 ∙ share

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An Out-of-the-box Full-network Embedding for Convolutional Neural Networks

Transfer learning for feature extraction can be used to exploit deep rep...
05/22/2017 ∙ by Dario Garcia-Gasulla, et al. ∙ 0 ∙ share

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Medical Text Classification using Convolutional Neural Networks

We present an approach to automatically classify clinical text at a sent...
04/22/2017 ∙ by Mark Hughes, et al. ∙ 0 ∙ share

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On the Behavior of Convolutional Nets for Feature Extraction

Deep neural networks are representation learning techniques. During trai...
03/03/2017 ∙ by Dario Garcia-Gasulla, et al. ∙ 0 ∙ share

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Scalable Parallel Numerical Constraint Solver Using Global Load Balancing

We present a scalable parallel solver for numerical constraint satisfact...
05/18/2015 ∙ by Daisuke Ishii, et al. ∙ 0 ∙ share

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Scalable Parallel Numerical CSP Solver

We present a parallel solver for numerical constraint satisfaction probl...
11/06/2014 ∙ by Daisuke Ishii, et al. ∙ 0 ∙ share

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Toyotaro Suzumura

Featured Co-authors

Jie Chen

Pin-Yu Chen

Yi Zhou

Tengfei Ma

Satoshi Matsuoka

Dario Garcia-Gasulla

Irene Li

Eduard Ayguadé

Chun-Fu Chen

Yixin Li

Jesus Labarta

Efficient Scaling of Dynamic Graph Neural Networks

Finding All Bounded-Length Simple Cycles in a Directed Graph

Heterogeneous Graph Neural Networks for Multi-label Text Classification

Time-Efficient and High-Quality Graph Partitioning for Graph Dynamic Scaling

The Impact of COVID-19 on Flight Networks

Benchmarking Graph Data Management and Processing Systems: A Survey

Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincaré Embeddings

Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis

Towards Federated Graph Learning for Collaborative Financial Crimes Detection

Distributed Edge Partitioning for Trillion-edge Graphs

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs

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

An incremental local-first community detection method for dynamic graphs

Scalable attribute-aware network embedding with locality

Scalable attribute-aware network embedding with localily

System G Distributed Graph Database

Full-Network Embedding in a Multimodal Embedding Pipeline

Building Graph Representations of Deep Vector Embeddings

Can GAN Learn Topological Features of a Graph?

An Out-of-the-box Full-network Embedding for Convolutional Neural Networks

Medical Text Classification using Convolutional Neural Networks

On the Behavior of Convolutional Nets for Feature Extraction

Scalable Parallel Numerical Constraint Solver Using Global Load Balancing

Scalable Parallel Numerical CSP Solver