1. A method, comprising: determining a plurality of machine learning features in a computer network to collect at a learning data processor; receiving data corresponding to the plurality of features; aggregating the data; generating a statistical analysis of all collected features; performing a traffic reduction measure based on the statistical analysis; learning a probabilistic model of time evolution of the received feature data; and pushing the aggregated data for select features to interested learning machines associated with the computer network.