Pith Number
pith:NKUXPWVZ
pith:2019:NKUXPWVZH7JOZHPMOUQHKYHVPE
not attested
not anchored
not stored
refs pending
Do Subsampled Newton Methods Work for High-Dimensional Data?
arxiv:1902.04952 v2 · 2019-02-13 · stat.ML · cs.LG · math.OC
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NKUXPWVZH7JOZHPMOUQHKYHVPE}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
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claim
4
Citations
5
Replications
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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.
Receipt and verification
| First computed | 2026-05-17T23:47:01.873667Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6aa977dab93fd2ec9dec75207560f579389e19a4da607365d9f351c3edb5abc7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NKUXPWVZH7JOZHPMOUQHKYHVPE \
| 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: 6aa977dab93fd2ec9dec75207560f579389e19a4da607365d9f351c3edb5abc7
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "a91988e948e2523a65420d03df3ab16bef909a39580f87970b2aca74866c0da9",
"cross_cats_sorted": [
"cs.LG",
"math.OC"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2019-02-13T15:30:10Z",
"title_canon_sha256": "668db94dbf475ba6e68a9c367ffa200f2787cecb6346f511b8a6220314acfe8b"
},
"schema_version": "1.0",
"source": {
"id": "1902.04952",
"kind": "arxiv",
"version": 2
}
}