AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work uses the AUC bound as a differentiable, anomaly-free objective for directly optimizing continuous parameters of anomaly detection systems and demonstrates this framework by optimizing ensemble weights and introducing a learnable score-rescaling mechanism that adapts pseudo-anomaly scores, enabling optimizatio...
Results show that embedding-space geometry contains predictive information about anomaly detection performance while also highlighting the representation-dependent nature of inlier-only performance estimates.
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