학습 최적화 기술
연구내용
연구실적(논문/성과홍보/공개SW)
[International Conferences]
- SangMook Kim, SangMin Bae, Se-Young Yun, Hwanjun Song, “LG-FAL : Federated Active Learning Strategy using Local and Global Models”, ICML 2022 [Link]
- SangMook Kim, Wonyoung Shin, Soohyuk Jang, Hwanjun Song, Se-Young Yun, “FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning”, CIKM 2022 [Link]
- Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Son, Se-Young Yun, “Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty”, NeurIPS 2022 [Link]
[Domestic Conferences]
- 김상묵, 배상민, 엄성하, 윤세영, “연합학습에서 클래스 균형을 고려한 디바이스 스케줄링 알고리즘”, 한국컴퓨터종합학술대회, pp. 846-848, 2022. [Link]
- 이정현, 정민찬, 허남규, 윤세영, “그래프 신경망의 확률적 경사 소음의 통계적 분석”, 한국컴퓨터종합학술대회, pp. 1025-1027, 2022. [Link]
[Promotions]
[Open SW]
Acknowledgement
This work was supported by Institute for Information &
Communications Technology Promotion (IITP) grant funded
by the Korea government (MSIT) [No.2022-0-00871, Development of AI Autonomy and Knowledge Enhancement for AI Agent Collaboration).].