Adaptive optimization methods, such as AdaGrad , RMSProp , and Adam , are widely used in solving large-scale machine learning problems. A number of schemes have been proposed in the literature aiming at parallelizing them, based on communications …
The main challenge for adaptive regulation of linear-quadratic systems is the tradeoff between identification and control. An adaptive policy needs to address both the estimation of unknown dynamics parameters (exploration), as well as the regulation …