{
  "article_slug": "private-gradient-clipping",
  "claims": [
    {
      "id": "s1",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "1. Privacy noise is not the first modification"
    },
    {
      "id": "s2",
      "kind": "source_based_review",
      "sources": [
        "dl3-b-private-gradient-clipping-1",
        "dl3-b-private-gradient-clipping-2",
        "dl3-b-private-gradient-clipping-3",
        "dl3-b-private-gradient-clipping-4",
        "dl3-b-private-gradient-clipping-5",
        "dl3-b-private-gradient-clipping-6"
      ],
      "claim": "2. The primary records address different layers"
    },
    {
      "id": "s3",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "3. The protected unit determines the contribution"
    },
    {
      "id": "s4",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "4. Clipping and expectation do not commute"
    },
    {
      "id": "s5",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "5. A zero-mean perturbation cannot remove deterministic bias"
    },
    {
      "id": "s6",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "6. Threshold selection creates a bias-variance tradeoff"
    },
    {
      "id": "s7",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "7. Privacy accounting cannot be inferred from the plot"
    },
    {
      "id": "s8",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "8. Adaptive thresholds use information too"
    },
    {
      "id": "s9",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "9. Per-layer clipping changes the admissible shape"
    },
    {
      "id": "s10",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "10. Minority utility requires conditional diagnostics"
    },
    {
      "id": "s11",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "11. Optimizer state changes how distortion accumulates"
    },
    {
      "id": "s12",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "12. A useful experiment isolates the sources of error"
    },
    {
      "id": "s13",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "13. Exact controls bound the present claims"
    },
    {
      "id": "s14",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "14. Implications for reliable private learning"
    },
    {
      "id": "s15",
      "kind": "author_analysis_or_verification_proposal",
      "sources": [],
      "claim": "15. Loss normalization changes the apparent threshold"
    }
  ]
}