AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces Sparse Autoencoder Geometric Anchoring (SAGA), which converts a Sparse Autoencoder (SAE) trained at each task boundary into local, low-rank constraints on representation drift, and establishes its local relation to latent code matching, define its spectral truncation error, and derive a conditional...
SPIRAL is introduced, a novel TS2I transformation designed for TSAD that maps time series windows onto a two-arm Archimedean spiral, producing asymmetric representations that preserve temporal locality while eliminating redundancy with linear time complexity with respect to window length.
PRISM is introduced, a plug-and-play meta-workflow enabling systematic construction and evaluation of image-based representations for multivariate TSAD and channelization is identified - how the channel dimension of multi-channel images is constructed - as a critical and previously understudied design dimension.
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