We create, extend, and refine mathematical techniques in three major fields. We aim at a comprehensive, mathematically sound framework for learning transformation rules in abstract rewriting systems, we develop new methods for stochastic models addressing the often-observed problem of outliers in classification or stochastic time series, and we advance the field of learning theory in various respects.