Abstract: A system according to an embodiment optimizes communications with users using machine learning based models. The system receives user profile data for a set of users. For each user from the set of users, the system provides the user profile data as input to a machine learning based model and determines attributes describing the user, for example a measure of adherence rate for the user. The system ranks the set of users based on the predicted attributes. The system selects a subset of users from the set of users based on the ranking. For each selected user from the set of selected users, the system determines communication parameters for communicating with the selected user and sends a communication to the selected user based on the determined communication parameters.

Abstract: A system trains a neural network for predicting time for communicating with users. The system trains the neural network using user data for users that includes a communication time series and an event time series. The system trains the neural network by masking a portion of the time series data and provides the masked time series data as input to the neural network. The system executes the neural network to predict values of the masked portion of the time series data. The system determines a loss value based on the accuracy of the prediction of the masked portion of the time series data and adjusts parameters of the neural network to minimize the loss value. The system uses the trained neural network to predict timing for communicating with a particular user.

Abstract: A system uses a machine learning based model to select a channel for communicating with users. The system generates a feature vector based on a user profile of the user. The user profile data includes time series data describing past communications to users and past user actions. The system executes one or more machine learning based models, each machine learning based model configured to receive a feature vector describing a particular user and predict a likelihood of the particular user performing an expected user action responsive to a communication sent via the communication channel. The system selects a communication channel based on the results of the machine learning based models and sends a communication to the user via the selected communication channel.