Mixing Time Bounds for Asymmetric Random Walks on Hypercubes, Cycles, and Tori Using Coupling
Mixing time bounds for Markov chains play a central role in characterizing the sample complexity of learning and inference from correlated data. While the mixing behavior of symmetric random walks on standard graph structures such as cycles, tori, and hypercubes is well understood, the impact of transition asymmetry re...