Pith Number
pith:KD6RD6HL
pith:2018:KD6RD6HLIOXCKXVEZPJ27ULIQK
not attested
not anchored
not stored
refs pending
Gradient-based Optimization for Regression in the Functional Tensor-Train Format
arxiv:1801.00885 v2 · 2018-01-03 · stat.CO · math.OC · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{KD6RD6HLIOXCKXVEZPJ27ULIQK}
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 | 2026-05-18T00:04:59.812907Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
50fd11f8eb43ae255ea4cbd3afd16882b3168484673256ea0f15e85ca06c618a
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KD6RD6HLIOXCKXVEZPJ27ULIQK \
| 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: 50fd11f8eb43ae255ea4cbd3afd16882b3168484673256ea0f15e85ca06c618a
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c39fef791d82249c83860a4886cbc2c7cf661b6945a9b3f29d6e9f6da7d3b7c3",
"cross_cats_sorted": [
"math.OC",
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.CO",
"submitted_at": "2018-01-03T02:34:14Z",
"title_canon_sha256": "b42b0a3229225a4be8d1a07e80e6814fcf1149ae3c1130a465e4c9cabd4e5a0f"
},
"schema_version": "1.0",
"source": {
"id": "1801.00885",
"kind": "arxiv",
"version": 2
}
}