{
  "id": "0805.2362",
  "version": "v1",
  "published": "2008-05-15T17:25:03.000Z",
  "updated": "2008-05-15T17:25:03.000Z",
  "title": "An optimization problem on the sphere",
  "authors": [
    "Andreas Maurer"
  ],
  "categories": [
    "cs.LG",
    "cs.CG"
  ],
  "abstract": "We prove existence and uniqueness of the minimizer for the average geodesic distance to the points of a geodesically convex set on the sphere. This implies a corresponding existence and uniqueness result for an optimal algorithm for halfspace learning, when data and target functions are drawn from the uniform distribution.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2008-05-15T17:25:03.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "optimization problem",
      "average geodesic distance",
      "uniform distribution",
      "target functions",
      "optimal algorithm"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2008arXiv0805.2362M"
    }
  }
}