SALZA: Soft algorithmic complexity estimates for clustering and   causality inference
  A complete set of practical estimators for the conditional, simple and joint algorihmic complexities is presented, from which a semi-metric is derived. Also, new directed information estimators are proposed that are applied to causality inference on Directed Acyclic Graphs. The performances of these estimators are investigated and shown to compare well with respect to the state-of-the-art Normalized Compression Distance (NCD). 
Marion Revolle and Cayre Fran\c{c}ois and Nicolas Le Bihan
cs.IT math.IT