Our arXiv paper on collaborative bandits over a network has been updated!
Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks
We have updated our arXiv paper on collaborative bandits over a network, with the new title Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks as well as several significant changes in the overall organization and experiments.
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.