activity
20232025
most citedGuP: Fast Subgraph Matching by Guard-based Pruning

43 citations · 44 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Meta-learning Representations for Learning from Multiple Annotators

Atsutoshi Kumagai, Tomoharu Iwata, Taishi Nishiyama +2

We propose a meta-learning method for learning from multiple noisy annotators. In many applications such as crowdsourcing services, labels for supervised learning are given by mult…

cs.LG2024

Meta-learning for Positive-unlabeled Classification

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

We propose a meta-learning method for positive and unlabeled (PU) classification, which improves the performance of binary classifiers obtained from only PU data in unseen target t…

cs.DB202343 cited

GuP: Fast Subgraph Matching by Guard-based Pruning

Junya Arai, Yasuhiro Fujiwara, Makoto Onizuka

Subgraph matching, which finds subgraphs isomorphic to a query, is the key to information retrieval from data represented as a graph. To avoid redundant exploration in the data, ex…

cs.LG2023

Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers

Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi +2

Regularized discrete optimal transport (OT) is a powerful tool to measure the distance between two discrete distributions that have been constructed from data samples on two differ…

cs.DB20231 cited

Scheduling Space Expander: An Extension of Concurrency Control for Data Ingestion Queries

Sho Nakazono, Hiroyuki Uchiyama, Yasuhiro Fujiwara +1

With the continuing advances of sensing devices and IoT/Telecom applications, database systems need to process data ingestion queries that update the sensor data frequently. Howeve…