2 citations · 2 across the 4 of their papers we have counts for
4 papers
Hierarchical Model Selection for Graph Neural Netoworks
Yuga Oishi, Ken Kaneiwa
Node classification on graph data is a major problem, and various graph neural networks (GNNs) have been proposed. Variants of GNNs such as H2GCN and CPF outperform graph convoluti…
The Completeness of Reasoning Algorithms for Clause Sets in Description Logic ALC
Daiki Takahashi, Ken Kaneiwa
On the Semantic Web, metadata and ontologies are used to enable computers to read data. The Web Ontology Language (OWL) has been proposed as a standard ontological language, and va…
Block-Segmentation Vectors for Arousal Prediction using Semi-supervised Learning
Yuki Odaka, Ken Kaneiwa
To handle emotional expressions in computer applications, Russell's circum- plex model has been useful for representing emotions according to valence and arousal. In SentiWordNet,…
Skip Vectors for RDF Data: Extraction Based on the Complexity of Feature Patterns
Yota Minami, Ken Kaneiwa
The Resource Description Framework (RDF) is a framework for describing metadata, such as attributes and relationships of resources on the Web. Machine learning tasks for RDF graphs…