AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes an end-to-end pipeline for data-driven decision making in which constraints and objectives are directly learned from data using machine learning, and the trained models are embedded in an optimization formulation.
This work proposes integrating and advancing LLM and optimization modeling to empower organizational decision-makers to model and solve such complex problems without requiring deep expertise in optimization, thereby enabling much more widespread improved decision-making and increasing by orders of magnitude the benefit...
This work mathematically demonstrates that standard sampling methods fail efficiently for rare violations, motivating a direct structural approach and introduces an exact sampling procedure and closed-form risk statistics that provide feature-level attributions without requiring repetitive random trials or complex samp...
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