pith:MDJRXQ3V
High-Probability Convergence Guarantees of Decentralized SGD
Decentralized SGD converges in high probability under the same cost conditions as mean-squared error convergence.
arxiv:2510.06141 v6 · 2025-10-07 · cs.LG · cs.MA · math.OC
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\pithnumber{MDJRXQ3VZX2YYDOUQKAZ5ZIR7E}
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Claims
We show that DSGD converges in HP under the same conditions on the cost as in the MSE sense, removing the restrictive assumptions used in prior works. Our sharp analysis yields order-optimal rates for both non-convex and strongly convex costs and establishes a linear speed-up in the number of users.
The noise is light-tailed so that moment-generating functions exist and can be bounded, which is weaker than uniform gradient bounds but still requires a specific tail condition on the stochastic gradients that may not hold for arbitrary data distributions.
Decentralized SGD achieves high-probability convergence with order-optimal rates and linear speedup in the number of users under standard smoothness and convexity conditions on the cost function.
Receipt and verification
| First computed | 2026-05-22T01:03:47.739841Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
60d31bc375cdf58c0dd482819ee511f92ce49bc55800c56ba74de8ebc9d5a9fd
Aliases
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MDJRXQ3VZX2YYDOUQKAZ5ZIR7E \
| 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: 60d31bc375cdf58c0dd482819ee511f92ce49bc55800c56ba74de8ebc9d5a9fd
Canonical record JSON
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