Matrix Supermartingales and Randomized Matrix Concentration Inequalities

Wang, Hongjian, Ramdas, Aaditya

arXiv.org Machine Learning 

These inequalities are often randomized in a way that renders them strictly tighter than existing deterministic results in the literature, are typically expressed in the Loewner order, and are sometimes valid at arbitrary data-dependent stopping times. Along the way, we explore the theory of matrix supermartingales and maximal inequalities, potentially of independent interest.