Abstract: A deep state space generative model is augmented with intervention prediction. The state space model provides a principled way to capture the interactions among observations, interventions, critical event occurrences, true states, and associated uncertainty. The state space model can include a discrete-time hazard rate model that provides flexible fitting of general survival time distributions. The state space model can output a joint prediction of event risk, observation and intervention trajectories based on patterns in temporal progressions, and correlations between past measurements and interventions.

Abstract: A computer-implemented technique can include obtaining a vector-based language model associating elements of an unlabeled corpus that have similar meanings, training a machine-learning classifier using the vector-based language model and a labeled corpus of text that has been annotated as having a particular level of abusiveness, obtaining a text, determining a prediction for the text using the machine-learning classifier, the prediction being indicative of a level of abusiveness of the text, and based on the level of abusiveness of the text, selectively outputting a recommended action with respect to the text.