Name
Abstract | ||
|---|---|---|
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). |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Information Theory | Discrete mathematics,Causality,Inference,Normalized compression distance,Directed acyclic graph,Cluster analysis,Algorithmic complexity,Mathematics,Estimator |
DocType | Volume | Citations |
Journal | abs/1607.05144 | 1 |
PageRank | References | Authors |
0.43 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marion Revolle | 1 | 1 | 0.43 |
| Francois Cayre | 2 | 244 | 18.86 |
| Nicolas Le Bihan | 3 | 254 | 23.35 |