2601.05669v1.pdf

{
  "dorsal/arxiv": [
    {
      "date_modified": "2026-02-17T05:53:04.654000Z",
      "hash": "5815432ed203e374e077eeb7376cc140c2a69f87cf9810ec82d7a03332dbc480",
      "id": "5714ba00-24f7-4582-83ee-47a4ff6335d0",
      "source": {
        "execution_id": "d04fc028-1b32-408d-a417-b0c540c696dd",
        "id": "arXiv Dataset",
        "type": "Model",
        "variant": "snapshot-2026-01-17",
        "version": "0.1.0"
      },
      "user_id": 1000002
    }
  ],
  "file/base": {
    "record": {
      "extension": ".pdf",
      "hash": "5815432ed203e374e077eeb7376cc140c2a69f87cf9810ec82d7a03332dbc480",
      "media_type": "application/pdf",
      "media_type_prefix": "application",
      "name": "2601.05669v1.pdf",
      "size": 737788
    },
    "source": {
      "execution_id": "2e1277af-566f-4aea-983d-36285972b265",
      "id": "file/base",
      "type": "Model",
      "version": "1.0.0"
    }
  },
  "file/pdf": {
    "private": false,
    "record": {
      "keywords": [],
      "page_count": 52,
      "producer": "pikepdf 8.15.1",
      "title": "Minimax Optimal Robust Sparse Regression with Heavy-Tailed Designs: A Gradient-Based Approach",
      "version": "1.7"
    },
    "source": {
      "execution_id": "85ca0ba1-e0ed-4573-8d4e-42db0e2fb644",
      "id": "dorsal/pdf",
      "type": "Model",
      "version": "1.1.0"
    }
  }
}