1. A method comprising: using one or more computers, during an offline period, initially determining a set of serving thresholds to be utilized in online advertisement serving, wherein a serving threshold is associated with a minimum anticipated click through rate; using one or more computer computers, during an offline period, initially determining a set of delivery policies, wherein a delivery policy is associated with one or more rules relating to serving of advertisements in accordance with required or optimal distribution of advertising inventory across serving opportunities; using one or more computers, during, and based at least in part on information obtained during, an online period, adjusting at least one of the set of serving thresholds to determine at least one adjusted serving threshold, and adjusting at least one of the set of delivery policies to determine at least one adjusted delivery policy; and using one or more computers, during an online period, utilizing a machine learning-based model in decision-making with regard to serving of online advertisements in connection with serving opportunities based at least in part on the at least one adjusted serving threshold and the at least one adjusted delivery policy, wherein the machine learning-based model is trained during an offline period, wherein an online period is a period of active advertisement serving in which the model is utilized.