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 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.