no code implementations • 29 Apr 2024 • Yongjin Yang, Sihyeon Kim, Sangmook Kim, Gyubok Lee, Se-Young Yun, Edward Choi
Incorporating unanswerable questions into EHR QA systems is crucial for testing the trustworthiness of a system, as providing non-existent responses can mislead doctors in their diagnoses.
no code implementations • 24 Aug 2023 • Gihun Lee, Minchan Jeong, Sangmook Kim, Jaehoon Oh, Se-Young Yun
FedSOL is designed to identify gradients of local objectives that are inherently orthogonal to directions affecting the proximal objective.
1 code implementation • CVPR 2023 • Sangmook Kim, Sangmin Bae, Hwanjun Song, Se-Young Yun
In this work, we first demonstrate that the superiority of two selector models depends on the global and local inter-class diversity.
2 code implementations • 7 Dec 2022 • Gihun Lee, Sangmook Kim, Joonkee Kim, Se-Young Yun
Cell segmentation is a fundamental task for computational biology analysis.
1 code implementation • 3 May 2022 • Sangmook Kim, Wonyoung Shin, Soohyuk Jang, Hwanjun Song, Se-Young Yun
Robustness is becoming another important challenge of federated learning in that the data collection process in each client is naturally accompanied by noisy labels.
1 code implementation • ICLR 2022 • Jaehoon Oh, Sangmook Kim, Se-Young Yun
Based on this observation, we propose a novel federated learning algorithm, coined FedBABU, which only updates the body of the model during federated training (i. e., the head is randomly initialized and never updated), and the head is fine-tuned for personalization during the evaluation process.
3 code implementations • 4 Jun 2021 • Jaehoon Oh, Sangmook Kim, Se-Young Yun
Based on this observation, we propose a novel federated learning algorithm, coined FedBABU, which only updates the body of the model during federated training (i. e., the head is randomly initialized and never updated), and the head is fine-tuned for personalization during the evaluation process.