papers
Publications (2)
cs.RO2026
Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences
Taehyung Kim, Gwangmo Lee, Minjun Chang +2
The paper proposes Preference-based REward Clustering (PREC), a method that groups users with similar preferences and learns a compact set of reward models from binary feedback to…
#human-robot interaction#preference learning#reward modeling#policy clustering
cs.DS2018
DISPATCH: An Optimally-Competitive Algorithm for Maximum Online Perfect Bipartite Matching with i.i.d. Arrivals
Minjun Chang, Dorit S. Hochbaum, Quico Spaen +1
This work presents an optimally-competitive algorithm for the problem of maximum weighted online perfect bipartite matching with i.i.d. arrivals. In this problem, we are given a kn…