NP4G : Network Programming for Generalization

1 code implementation • 8 Dec 2022 • Shoichiro Hara, Yuji Watanabe

Because the proposed method can realize "sequence", "selection", and "iteration" in programming and can satisfy the conditions of the structured program theorem, it is expected that NP4G is a method automatically acquire any programs by inductive inference.

Towards Federated Graph Learning for Collaborative Financial Crimes Detection

no code implementations • 19 Sep 2019 • Toyotaro Suzumura, Yi Zhou, Natahalie Baracaldo, Guangnan Ye, Keith Houck, Ryo Kawahara, Ali Anwar, Lucia Larise Stavarache, Yuji Watanabe, Pablo Loyola, Daniel Klyashtorny, Heiko Ludwig, Kumar Bhaskaran

Advances in technology used in this domain, including machine learning based approaches, can improve upon the effectiveness of financial institutions' existing processes, however, a key challenge that most financial institutions continue to face is that they address financial crimes in isolation without any insight from other firms.

Federated Learning Graph Learning

Villani at SemEval-2018 Task 8: Semantic Extraction from Cybersecurity Reports using Representation Learning

no code implementations • SEMEVAL 2018 • Pablo Loyola, Kugamoorthy Gajananan, Yuji Watanabe, Fumiko Satoh

In this paper, we describe our proposal for the task of Semantic Extraction from Cybersecurity Reports.

Representation Learning