AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The results show that sharing observations across objectives and ignoring irrelevant objective-wise distinctions can substantially reduce the sampling cost, as confirmed by experiments on synthetic and real-world tasks.
Verifying LLM-generated answers under a shared computational budget requires jointly deciding which candidates to inspect and which verification attributes to evaluate. We formulate this problem as multi-attribute good-arm identification under a global budget: each candidate is an arm evaluated along several costly att...
An inverse optimization perspective for OM is provided by reformulating it as an opinion minimization (OMin) problem, whose objective function holds succinct expression and desired properties and introduces a bounded estimation scheme (BES) that can estimate the objective function of OMin with bounded error in Õ(kn+m)...
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