{
  "id": "adrs14-cvp-197",
  "categoryId": "cvp-approximate-euclidean-parameterized",
  "paperId": "paper-86925aff6e6c",
  "year": 2015,
  "date": "2014-12-26",
  "time": {
    "coefficient": null,
    "expression": "2^{n+o(n)} for approximation factor γ = 1.97"
  },
  "space": {
    "coefficient": 1,
    "expression": "2^{n+o(n)}"
  },
  "tags": [
    "approximate search",
    "discrete Gaussian"
  ],
  "review": {
    "status": "source-checked"
  },
  "certificate": {
    "status": "not-provided",
    "lean": null
  },
  "notes": "The first arXiv abstract states a 1.97-approximate Euclidean search-CVP algorithm from discrete Gaussian sampling. The approximation factor is an entry parameter; this guarantee is not ranked against rows with another factor or a parameter-dependent cost. Exact CVP at the same leading time exponent appears in the later ADS paper.",
  "extra": {
    "norm": "Euclidean ℓ₂",
    "approximation": "γ = 1.97 (equivalently δ = 0.97)",
    "preprocessing": "Included",
    "success": "Randomized approximation; high-probability success",
    "timeExponentAtStatedGuarantee": "1"
  },
  "evidence": {
    "url": "https://arxiv.org/abs/1412.7994v1",
    "locator": "Abstract, CVP consequence of discrete Gaussian sampling",
    "sourceVersion": "arXiv:1412.7994v1, 26 December 2014"
  }
}