1. In a system to generate personalized recommendations with improved utilization of system hardware resources by using localized regularization, a method implemented by one or more computing devices, the method comprising: obtaining, by the one or more computing devices, known values for each item in a first subset of a set of items, the known values corresponding to one of multiple users of the system; identifying, by the one or more computing devices, a second subset of the set of items, each item in the second subset having an unknown value; generating, by the one or more computing devices for each item in the second item subset, a value for the item based on localized regularization that is personalized to the user individually from the multiple users, the generating including reducing an error between values of one or more of the first subset of items and computed values produced by a data model representing the values of the set of items by reducing a value that is a sum of: the error between values of the one or more of the first subset of items and computed values produced by the data model representing the values of the set of items, and the error resulting from introduction of additional information that is added by the data model; and taking, by the one or more computing devices based on the generated values for the items in the second item subset, one or more actions personalized to the user.