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End-to-end Optimization of Single-Shot Quantum Machine Learning for Bayesian Inference
We introduce an end-to-end optimization strategy for quantum machine learning that directly targets performance under finite measurement resources, where learning objectives are defined directly at the level of task performance. The method is applied on a Bayesian quantum metrology task since it pro
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