1. One or more computer-storage hardware devices having computer-executable instructions embodied thereon that, when executed by a computing device, cause the computing device to perform a method of determining relevant advertisements with a machine learning model based on a query, the method comprising: receiving training data for training a machine learning model, the training data comprising information indicating relevance between a set of reference and target documents, the documents comprising one or more training terms; determining one or more training data feature sets and corresponding training data feature values from the training terms of the training data, each feature set and values associated with a training term; generating, based on the training data feature sets and corresponding values, a cross-joined feature set of features comprising a combined first feature of a reference-document data feature and a second, different feature of a target-document feature; training the machine learning model by determining a set of weight parameters for each of the training terms by applying the one or more of the training feature sets, the cross-joined feature set, and values associated with the training term to the model; in response to a query, utilizing the model to determine a final measure of relevance between a query-target document and the query; and based on the final measure of relevance, causing the query-target document to be presented.
10. The one or more computer-storage hardware devices of claim 1 , wherein the machine learning model comprises an L-1 regularized logistic regression model.