Basic Information
Name: Ken Nishida
Affiliation: Graduate School of Information Science and Technology, Hokkaido University
Education
- High School: Toyo High School
- Undergraduate: Faculty of Engineering, Hokkaido University (Graduated 2023)
- Graduate School: Graduate School of Information Science and Technology, Hokkaido University (Expected Graduation 2025)
Laboratories
Affiliation: Information Knowledge Networks Laboratory
Collaborative Research: Hayashi Laboratory, University of Tokyo
Social Media
Research
Research Overview: Multi-label Classification
Multi-label classification is a task that classifies data points that may be assigned multiple labels simultaneously...
Research Overview: Multi-label Classification
Multi-label classification is a task that classifies data points that may be assigned multiple labels simultaneously. Unlike simple classification problems with a single label, multi-label classification can have multiple labels associated with each data point.
For example, in image classification, multi-label classification assigns multiple labels to an image when it represents different objects or attributes simultaneously. For instance, an image of a dog might be labeled with both "dog" and "walking."
Multi-label classification is used in various applications. For instance, in text classification, it is used when a document is related to multiple topics. It is also applied in music and video classification to predict labels associated with multiple genres or attributes.
Publications
- Ken Nishida, Kojiro Machi, Kazuma Onishi, Katsuhiko Hayashi, Hidetaka Kamigaito. Multi-label Learning with Random Circular Vectors. arXiv, July 2024 [Paper]
- Ken Nishida, Katsuhiko Hayashi, Kojiro Machi, Hidetaka Kamigaito. Multi-label Classification using Circular Vectors. IPSJ 258th NL Research Meeting, December 2023 [Paper] [Slide]
- Ken Nishida, Katsuhiko Hayashi, Hidetaka Kamigaito. Efficient Large-scale Multi-label Classification with Circular Holographic Reduced Representations. 18th NLP Young Researchers Symposium (YANS), August 2023 [Poster]
Internships and Experience
Click the button below to see more details about my internships and experience...
Sony
Position: Machine Learning Specialist
Duration: 3 weeks, February 2024
Worked on advanced technology development and application development utilizing AI/machine learning to enhance the value of Sony products, various services, and applications.
NTT Docomo
Position: Marketing
Duration: 2 weeks, August 2023
Worked on service growth and expansion for "Cabonew Record," a service that aims to solve social issues through a member base.
Archibase
Position: Engineer
Duration: 2 months, April~May 2023
Developed a job support site specializing in construction and equipment engineers.
Awards
The 18th YANS
Award: Sponsor Award
The 258th NL Research Meeting, IPSJ
Award: Young Researcher Encouragement Award
ACL 2024 Workshop Accepted
Award: Paper Acceptance
News
Stay tuned for the latest updates and announcements.