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pith:2026:CLKGG7GH3AZD7NMO22XQLBJ7OR
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Constrained Policy Optimization with Cantelli-Bounded Value-at-Risk

Jan-Peter Calliess, Rohan Tangri

VaR-CPO approximates Value-at-Risk constraints via Cantelli's inequality to guarantee zero violations during training in feasible reinforcement learning environments.

arxiv:2601.22993 v4 · 2026-01-30 · cs.LG · stat.ML

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4 Citations open
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Claims

C1strongest claim

VaR-CPO achieves zero constraint violations during training in feasible environments, a property baseline methods fail to uphold, while providing worst-case bounds for policy improvement and constraint violation.

C2weakest assumption

The Cantelli inequality provides a sufficiently tight and conservative approximation to the true VaR constraint so that enforcing the bound still guarantees the original probabilistic constraint in practice.

C3one line summary

VaR-CPO approximates non-differentiable VaR constraints via Cantelli's inequality to enable safe, sample-efficient policy optimization with zero training violations in feasible environments.

Formal links

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Receipt and verification
First computed 2026-06-30T01:17:33.333863Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

12d4637cc7d8323fb58ed6af05853f747e55a2b67d4353530956dd25adbf10a5

Aliases

arxiv: 2601.22993 · arxiv_version: 2601.22993v4 · doi: 10.48550/arxiv.2601.22993 · pith_short_12: CLKGG7GH3AZD · pith_short_16: CLKGG7GH3AZD7NMO · pith_short_8: CLKGG7GH
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CLKGG7GH3AZD7NMO22XQLBJ7OR \
  | 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: 12d4637cc7d8323fb58ed6af05853f747e55a2b67d4353530956dd25adbf10a5
Canonical record JSON
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    "cross_cats_sorted": [
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-01-30T13:57:47Z",
    "title_canon_sha256": "30ce4acde7984652dff459c97f283d90840781c4c1a41d0540b94b58f3c4c83c"
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