On the sample complexity of quantum Boltzmann machine learning

Pot Grab Abstract Quantum Boltzmann machines (QBMs) are machine-learning models for both classical and quantum data.We give an operational definition of QBM learning in terms of the difference in expectation values between the model and target, taking into account the polynomial size of the data set.By using the relative entropy as a loss function,

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Surgical and clinical efficacy of minimally invasive sacroiliac joint fusion surgery: a meta-analysis protocol

Introduction Sacroiliac joint (SIJ) dysfunction has been shown to cause significant morbidity.Current treatment includes conservative management and surgical intervention.Previously published data reporting clinical Extensions and surgical outcomes reached conflicting conclusions.This protocol aims to conduct a meta-analysis to determine fusion rat

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Establishment of microbial model communities capable of removing trace organic chemicals for biotransformation mechanisms research

Abstract Background Removal of trace organic chemicals (TOrCs) in aquatic environments has been intensively studied.Some members of natural microbial communities play a vital role in transforming chemical contaminants, however, complex microbial interactions impede us from gaining adequate understanding of TOrC biotransformation mechanisms.To simpl

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