The bandit problem with graph feedback, proposed in [Mannor and Shamir, NeurIPS 2011], is modeled by a directed graphG = (V,E) where V is the collection of bandit arms, and once an arm is triggered, all its incident arms are observed.
Foreffectiveknowledge transfer,weadopt the idea of domain classifier so that student training is guided by discriminative features invariant totherepresentational space shift between teacher andstudent.
Existing deeplearning-based demoiréing methods trainedonlargescaledatasets are limited in handling various complex moiré patterns, and mainly focus on demoiréing of photos taken of digital displays.