Byeonghu NA > Member | 카이스트 응용인공지능 연구실

Research Interest

Machine learning
Deep Generative Model: Diffusion Model, Variational Autoencoder
Insufficient/incomplete Dataset: Learning with Noisy Labels, Domain Adaptation, Active Learning, Positive-Unlabeled Learning
Scene Text Recognition (OCR)

Education

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Mar. 2021 ~ )

Doctoral Degree Program in Industrial and Systems Engineering, AAILab
Academic Advisor: Professor Il-Chul Moon

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Feb. 2019 - Feb. 2021)

Master's Degree Program in Industrial and Systems Engineering, AAILab
Academic Advisor: Professor Il-Chul Moon

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Mar. 2014 - Feb. 2019)

Bachelor of Science in Mathematical Sciences
Bachelor of Science in Industrial and Systems Engineering

Publication

International Conference

Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon, Label-Noise Robust Diffusion Models, International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024
Yeongmin Kim, Byeonghu Na, JoonHo Jang, Minsang Park, Dongjun Kim, Wanmo Kang, Il-Chul Moon, Training Unbiased Diffusion Models From Biased Dataset, International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024
HeeSun Bae, Seungjae Shin, Byeonghu Na, Il-chul Moon, Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning, International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024
Seungjae Shin, Heesun Bae, Byeonghu Na, Yoon-Yeong Kim, Il-Chul Moon, Unknown Domain Inconsistency Minimization for Domain Generalization, International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024
Byeonghu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoon-Yeong Kim, and Il-Chul Moon. 2020. Deep Generative Positive-Unlabeled Learning under Selection Bias. In The 29th ACM International Conference on Information and Knowledge Management (CIKM ’20), October 19–23, 2020, Virtual Event, Ireland.
HeeSun Bae*, Seungjae Shin*, Byeonghu Na, JoonHo Jang, Kyungwoo Song, and Il-Chul Moon. 2022. From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model. In The 39th International Conference on Machine Learning (ICML 2022), July 17-23, 2022, Baltimore, Maryland, USA.
Seungjae Shin, Byeonghu Na, HeeSun Bae, JoonHo Jang, Hyemi Kim, Kyungwoo Song, Youngjae Cho, and Il-Chul Moon. 2022. Improving Group-based Robustness and Calibration via Ordered Risk and Confidence Regularization. In The Workshop on Spurious Correlations, Invariance, and Stability, International Conference on Machine Learning (SCIS at ICML 2022), July 22, 2022, Baltimore, Maryland, USA.
Byeonghu Na, Yoonsik Kim, and Sungrae Park. 2022. Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features. In European Conference on Computer Vision (ECCV 2022), October 23-27, 2022, Tel-Aviv, Israel.
JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, and Il-Chull Moon. 2022. Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation. In The Conference on Neural Information Processing Systems (NeurIPS 2022), Nov 28-Dec 9, 2022, New Orleans, USA.
Dongjoun Kim*, Byeonghu Na*, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, and Il-Chul Moon. 2022. Maximum Likelihood Training of Implicit Nonlinear Diffusion Models. In The Conference on Neural Information Processing Systems (NeurIPS 2022), Nov 28-Dec 9, 2022, New Orleans, USA.
Yoon-Yeong Kim*, Youngjae Cho*, JoonHo Jang, Byeonghu Na, Yeongmin Kim, Kyungwoo Song, Wanmo Kang, Il-Chul Moon, SAAL: Sharpness-Aware Active Learning, In The 40th International Conference on Machine Learning (ICML 2023), Jul 25-27, 2023, Hawaii, USA.
Suhyeon Jo, DongHyeok Shin, Byeonghu Na, JoonHo Jang, and Il-Chul Moon. 2023. Hierarchical Multi-Label Classification with Partial Labels and Unknown Hierarchy. In The 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023), October 21–25, 2023, Birmingham, United Kingdom.

Domestic Conference

신승재, 나병후, 신동혁, 나영연, 문일철 (2017. 12) 인공 신경망 기반 뉴스기사의 토픽 분석 및 문서 분류 동시 수행 모델 개발, 한국정보과학회

Award

관정 국내대학원 장학생, 관정이종환장학재단, 2021 - 2022.
SIGIR Student Travel Grant, SIGIR, 2020.
김영한 글로벌리더 장학생, KAIST, 2020.
Summa Cum Laude, KAIST, 2019.
학부생부문 최우수상, KSC2017 학부생 논문경진대회, 2017.
이공계 국가우수장학금, 한국장학재단, 2014 - 2017.
고교 상상 장학생, KT&G 장학재단, 2012 - 2013.

Members

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