Pith Number
pith:IITVCRQV
pith:2020:IITVCRQVG2MS5SDPU5ZM5U74Y7
not attested
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not stored
refs pending
A Gradient-based Bilevel Optimization Approach for Tuning Hyperparameters in Machine Learning
arxiv:2007.11022 v1 · 2020-07-21 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IITVCRQVG2MS5SDPU5ZM5U74Y7}
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Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
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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.
Cited by
Linear Convergence Analysis of Single-loop Algorithm for Bilevel Optimization via Small-gain Theorem
Receipt and verification
| First computed | 2026-07-05T01:21:21.775022Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
422751461536992ec86fa772ced3fcc7f2cf437d82a8d1a8bcd42b75e3686ff6
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IITVCRQVG2MS5SDPU5ZM5U74Y7 \
| 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: 422751461536992ec86fa772ced3fcc7f2cf437d82a8d1a8bcd42b75e3686ff6
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f9b5888affb907efafeade231f7a9558d1d5acf1b50fd3fe72be4ab43c39d7ce",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2020-07-21T18:15:08Z",
"title_canon_sha256": "3ed6c11e729a31607b763f237799c9e9aceb3b37b67eaff46ed373e3eeeadf16"
},
"schema_version": "1.0",
"source": {
"id": "2007.11022",
"kind": "arxiv",
"version": 1
}
}