Graph cut algorithms are very popular in image segmentation approaches. However, the detailed parts of the foreground are not segmented well in graph cut minimization.There are basically two reasons of inadequate segmentations: (i) Data smoothness relationship of graph energy. (ii) Shrinking bias which is the bias towards shorter paths. This paper improves the foreground segmentation by integra...

We study a non-parametric multi-armed bandit problem with stochastic covariates, where key complexity driver is the smoothness of payoff functions respect to covariates. Previous studies have focused on deriving minimax-optimal algorithms in cases it priori known how smooth are. In practice, however, typically not advance, and misspecification may severely deteriorate performance existing metho...