LNO-QRD prunes network deployment candidates using law residuals, symmetry quotienting, and dominance before policy ranking, reducing candidate sets while preserving near-oracle performance.
Network slicing for 5g with sdn/nfv: Con- cepts, architectures, and challenges,
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Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control
LNO-QRD prunes network deployment candidates using law residuals, symmetry quotienting, and dominance before policy ranking, reducing candidate sets while preserving near-oracle performance.