pith:AEK7UWYQ
Stochastic Zeroth-Order Optimization Under Heavy-Tailed Noise
Clipped scalar directional estimates let zeroth-order methods find stationary points under heavy-tailed noise with near-optimal query rates.
arxiv:2605.17394 v1 · 2026-05-17 · math.OC
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Claims
Under sample-wise smoothness and a weak-L_p tail condition on sample-gradient noise, RSC-ZO finds an ε-stationary point with high probability using Õ(d^{p/2(p-1)} ε^{-(3p-2)/(p-1)}) noisy function evaluations.
That weak-L_p control of the sample gradient noise can be transferred to the scalar directional finite-difference estimates without additional assumptions that would invalidate the high-probability bound (abstract states this transfer is nontrivial and is the key technical step).
RSC-ZO achieves high-probability ε-stationary points for stochastic ZO optimization under weak-L_p heavy-tailed noise with Õ(d^{p/2(p-1)} ε^{-(3p-2)/(p-1)}) function queries.
References
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Receipt and verification
| First computed | 2026-05-20T00:03:56.299172Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0115fa5b10b82029f5d5f93235b5c5be08e0ed53946f2b85378782343a2548b8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/AEK7UWYQXAQCT5OV7EZDLNOFXY \
| 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: 0115fa5b10b82029f5d5f93235b5c5be08e0ed53946f2b85378782343a2548b8
Canonical record JSON
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