A Novel Switching Scheme Between Adaptive Information Algorithms
Switching approaches can improve the performance of adaptive schemes, however a data driven criterion to accomplish the task is unclear. In this paper, we propose a new optimization criterion for switching which is estimated directly from data. We apply the method to the recently introduced MEE and MEE-SAS algorithms. Using this novel switching scheme, we develop a single algorithm which effectively combines the strengths of MEE and MEE-SAS without sacrificing the simplicity and stability properties of MEE. We explain these results analytically, and through simulations.