{
  "id": "2009.13500",
  "version": "v1",
  "published": "2020-09-28T17:47:25.000Z",
  "updated": "2020-09-28T17:47:25.000Z",
  "title": "A priori estimates for classification problems using neural networks",
  "authors": [
    "Weinan E",
    "Stephan Wojtowytsch"
  ],
  "categories": [
    "stat.ML",
    "cs.LG",
    "cs.NA",
    "math.NA"
  ],
  "abstract": "We consider binary and multi-class classification problems using hypothesis classes of neural networks. For a given hypothesis class, we use Rademacher complexity estimates and direct approximation theorems to obtain a priori error estimates for regularized loss functionals.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2020-09-28T17:47:25.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "68T07",
      "60-08"
    ],
    "keywords": [
      "neural networks",
      "priori estimates",
      "hypothesis class",
      "direct approximation theorems",
      "rademacher complexity estimates"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}