Pith Number

pith:52NKXIGF

pith:2023:52NKXIGFARBDITXTQAT57QLXEH

not attested not anchored not stored refs pending

Analysis of the expected $L_2$ error of an over-parametrized deep neural network estimate learned by gradient descent without regularization

Michael Kohler, Selina Drews

arxiv:2311.14609 v1 · 2023-11-24 · stat.ML · cs.LG

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\usepackage{pith}
\pithnumber{52NKXIGFARBDITXTQAT57QLXEH}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Cited by

1 paper in Pith

Minimax-Optimal Generalization Bounds for Smooth Deep Neural Networks Trained by (Stochastic) Gradient Descent

Receipt and verification

First computed	2026-07-05T07:16:21.764923Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ee9aaba0c50442344ef38027dfc17721d4f499f2d7469e681fbe6bae68a05969

Aliases

arxiv: 2311.14609 · arxiv_version: 2311.14609v1 · doi: 10.48550/arxiv.2311.14609 · pith_short_12: 52NKXIGFARBD · pith_short_16: 52NKXIGFARBDITXT · pith_short_8: 52NKXIGF

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/52NKXIGFARBDITXTQAT57QLXEH \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ee9aaba0c50442344ef38027dfc17721d4f499f2d7469e681fbe6bae68a05969

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "607f25cbd986d4f7421a806aab7250a0e9bb5fab5a3d1c0260e78db1a2e499d3",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "stat.ML",
    "submitted_at": "2023-11-24T17:04:21Z",
    "title_canon_sha256": "ada92a62f56834a5f46e46695b0479626cf1767071a1c410c168e6b06bffa872"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2311.14609",
    "kind": "arxiv",
    "version": 1
  }
}