{
  "id": "1607.02330",
  "version": "v1",
  "published": "2016-07-08T12:02:36.000Z",
  "updated": "2016-07-08T12:02:36.000Z",
  "title": "Two Measures of Dependence",
  "authors": [
    "Amos Lapidoth",
    "Christoph Pfister"
  ],
  "comment": "5 pages; submitted to ICSEE 2016",
  "categories": [
    "cs.IT",
    "math.IT"
  ],
  "abstract": "Motivated by a distributed task-encoding problem, two closely related families of dependence measures are introduced. They are based on the R\\'enyi divergence of order {\\alpha} and the relative {\\alpha}-entropy, respectively, and both reduce to the mutual information when the parameter {\\alpha} is one. Their properties are studied and it is shown that the first measure shares many properties with mutual information, including the data-processing inequality. The second measure does not satisfy the data-processing inequality, but it appears naturally in the context of distributed task encoding.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2016-07-08T12:02:36.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "mutual information",
      "first measure shares",
      "data-processing inequality",
      "properties",
      "dependence measures"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 5,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}