One paper accepted to ICLR 2024!
Querying Easily Flip-flopped Samples for Deep Active Learning
One paper (Querying Easily Flip-flopped Samples for Deep Active Learning) is accepted to ICLR 2024! This is joint work with Seong Jin Cho (who led the entire project and did all the experiments!) (KAIST EE), Gwangsu Kim (JBNU Statistics), Jinwoo Shin (KAIST AI), and Chang D. Yoo (KAIST EE).
I’ll be attending in person. See you all at Vienna, Austria!
Junghyun Lee
PhD Student
PhD student at GSAI, KAIST, jointly advised by Prof. Se-Young Yun and Prof. Chulhee Yun. Interested in mathematical and theoretical AI, i.e., essentially any machine learning challenges necessitating mathematical analysis. Recently focused on statistical problems arising from RLHF, including interactive machine learning and low-dimensional structure recovery.