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 Profs. Se-Young Yun and Chulhee Yun. Research focuses on interactive machine learning, particularly at the intersection of RLHF and preference learning, and statistical analyses of large networks, with an emphasis on community detection. Broadly interested in mathematical and theoretical AI and related problems in mathematics.