AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces RAPTOR - a Role-Aware Private Training framework, which alternates shared and expert optimization and targets each failure directly, using expert-specific clipping and noise together with a public expected-owner denominator and a count-independent update schedule that avoids conditioning on private...
CutBackdoor is presented, the first parameter-supply-chain backdoor that uses cut circuit execution from CutQC as the deployment-time trigger against VQAs, and poisoned parameters preserve full-circuit validation performance while substantially increasing cut-path reconstruction error under noisy finite-shot circuit-cu...
This paper proposes a novel decentralized stochastic first-order optimization algorithm, which does not require second-order Hessian or Jacobian matrices, for the setting where the lower-level loss function is nonconvex but satisfies the Polyak–Łojasiewicz (PL) condition.
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