pith:UO6DAYQL
Accelerated Decentralized Constraint-Coupled Optimization: A Dual$^2$ Approach
A dual squared approach produces two accelerated algorithms for decentralized optimization with shared constraints that converge under milder conditions on the public cost function.
arxiv:2505.03719 v5 · 2025-05-06 · math.OC · cs.SY · eess.SY
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Record completeness
Claims
Both iD2A and MiD2A guarantee asymptotic convergence under a milder condition on h compared to existing algorithms; under additional assumptions they establish linear convergence rates and significantly lower communication and computational complexity bounds.
The network is undirected and connected, which is required for the information to propagate sufficiently for the dual updates to coordinate the shared constraint across all agents (stated in the problem formulation).
The Dual² approach produces iD2A and MiD2A gradient methods that achieve asymptotic convergence under milder conditions on the public function and linear rates with reduced communication and computation complexity.
Formal links
Receipt and verification
| First computed | 2026-06-25T01:18:34.824689Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
a3bc30620b18adbab8465b63ce65535b9adca0f5d50fb200a05f2a616e6a83c5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/UO6DAYQLDCW3VOCGLNR44ZKTLO \
| 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: a3bc30620b18adbab8465b63ce65535b9adca0f5d50fb200a05f2a616e6a83c5
Canonical record JSON
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