Pith Number

pith:SPEIT5LQ

pith:2026:SPEIT5LQ5YXVLXGLAUUVEYQWMD

not attested not anchored not stored refs pending

Inference of Online Newton Methods with Nesterov's Accelerated Sketching

Haoxuan Wang, Sen Na, Xinchen Du

An online Newton method with Nesterov-accelerated sketching provides global convergence and asymptotic normality for inference on streaming data at first-order complexity.

arxiv:2604.23436 v2 · 2026-04-25 · stat.ML · cs.LG · math.OC · stat.CO

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\usepackage{pith}
\pithnumber{SPEIT5LQ5YXVLXGLAUUVEYQWMD}

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Record completeness

1 Bitcoin timestamp

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.

Claims

C1strongest claim

we establish global almost-sure convergence, prove asymptotic normality of the last iterate with a limiting covariance characterized by a Lyapunov equation, and develop a fully online covariance estimator with non-asymptotic convergence guarantees.

C2weakest assumption

Under standard smoothness and moment conditions

C3one line summary

An accelerated sketched online Newton method with Hessian averaging achieves global almost-sure convergence, asymptotic normality via a Lyapunov covariance, and a fully online covariance estimator under standard conditions.

Receipt and verification

First computed	2026-06-01T01:02:40.651720Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

93c889f570ee2f55dccb052952621660ceb9a43404ae625d13429a855e720de5

Aliases

arxiv: 2604.23436 · arxiv_version: 2604.23436v2 · doi: 10.48550/arxiv.2604.23436 · pith_short_12: SPEIT5LQ5YXV · pith_short_16: SPEIT5LQ5YXVLXGL · pith_short_8: SPEIT5LQ

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/SPEIT5LQ5YXVLXGLAUUVEYQWMD \
  | 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: 93c889f570ee2f55dccb052952621660ceb9a43404ae625d13429a855e720de5

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4696375392698ea4bb7e0fcffce67f185b60a5ed857959a5fc3bc57a71d4afe1",
    "cross_cats_sorted": [
      "cs.LG",
      "math.OC",
      "stat.CO"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ML",
    "submitted_at": "2026-04-25T20:43:17Z",
    "title_canon_sha256": "d5c1d5af7abd0b36a2e899bbd79b0737d5eaaa792d3d8872f06ef191477270ce"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.23436",
    "kind": "arxiv",
    "version": 2
  }
}