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Addressing High-dimensional Biases in Information-theoretic Measure Estimators and Its Applications to Machine Learning
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 노영균 | - |
| dc.date.accessioned | 2024-12-05T18:00:21Z | - |
| dc.date.available | 2024-12-05T18:00:21Z | - |
| dc.date.issued | 2023-11-24 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/201159 | - |
| dc.title | Addressing High-dimensional Biases in Information-theoretic Measure Estimators and Its Applications to Machine Learning | - |
| dc.type | Conference | - |
| dc.citation.conferenceName | KIAS Center for AI and Natural Sciences Workshop | - |
| dc.citation.conferencePlace | Commodore Hotel, Gyeongju | - |
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Collections - 서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 2. Conference Papers
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Related Researcher
- Noh, Yung Kyun
- COLLEGE OF ENGINEERING (SCHOOL OF COMPUTER SCIENCE)