Dynamic Power management for known applications
Bayesian optimization (BO) can be used effectively to find optimal power management policies. BO was shown to be better than existing methods, i.e., imitation learning, reinforcement learning.
Uncertainty-aware online learning for unseen applications
Conformal prediction can reduce the learning overhead by (a) reducing the search space and (b) learning only when needed, to save power without loss in performance.