Accounting for Changes in the Distribution of Data

<div>Accomodating changes to the distribution of data in classification and inference procedures is an important</div><div>problem for statistics. For instance, statistical predictions often rely on the assumption that future data will follow the same distribution as past data, and predictions may fail when there is a change to the data generating process. In other cases, detecting changes to the distribution of data is of scientific interest itself. For example, when monitoring a patient's brain activity, a change may have serious health implications; and in cellular biology, characterizing differences between biological conditions is a key goal for experiments.</div>