Algorithm 3.

Gradient Ascent Implementation of the M-step

1:	Input: β(t), Qn(β; β(t))
2:	Parameter: Stepsize η > 0
3:	Output: Mn(β(t)) ← β(t) + η · ∇Qn(β(t); β(t))
	{The gradient is taken with respect to the first β(t) in Qn(β(t); β(t))}