A Details of mmTS for Exponential Families For a matrix (vector) M, we let M

The general form for an exponential family likelihood is still retained. The prior-to-posterior conversion simply involves updating the prior parameters with sufficient statistics from the data. The inequality is by Markov's inequality. This concludes the proof.C.1 Proof of Theorem 1 Since we have context generated by some random process, we instead turn to martingales. We see that the choice of action given observed context depends on past rounds.