The MIMO MAC admits canonical convex formulations solved via L-BFGS on per-tone Cholesky factors, yielding four solvers that match commercial performance while running up to 100x faster.
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CAMCO enforces policy constraints on multi-agent AI at deployment time via convex projection, risk-weighted Lagrangian shaping, and bounded-convergence negotiation, yielding zero violations and 92-97% utility in tested enterprise scenarios.
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Canonical Optimization for MIMO MAC Design
The MIMO MAC admits canonical convex formulations solved via L-BFGS on per-tone Cholesky factors, yielding four solvers that match commercial performance while running up to 100x faster.
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Safe and Policy-Compliant Multi-Agent Orchestration for Enterprise AI
CAMCO enforces policy constraints on multi-agent AI at deployment time via convex projection, risk-weighted Lagrangian shaping, and bounded-convergence negotiation, yielding zero violations and 92-97% utility in tested enterprise scenarios.