ON THE SAMPLE COMPLEXITY OF QUANTUM BOLTZMANN MACHINE LEARNING

On the sample complexity of quantum Boltzmann machine learning

Abstract Quantum Boltzmann machines (QBMs) are machine-learning models for both Foot Pad 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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Development of a Direct Headspace Collection Method from Arabidopsis Seedlings Using HS-SPME-GC-TOF-MS Analysis

Plants produce various volatile organic compounds (VOCs), which are thought to be a crucial factor in their interactions with harmful insects, plants and animals.Composition of VOCs may differ when plants are grown under different nutrient 4 Piece RAF Reclining Sectional conditions, i.e., macronutrient-deficient conditions.However, in plants, relat

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Ultrasonographic Measurement of Torsional Side Difference in Proximal Humerus Fractures and Humeral Shaft Fractures: Theoretical Background with Technical Notes for Clinical Implementation

Both nonoperative and operative treatment of proximal humerus fractures (PHF) and humeral shaft fractures can result in torsional side differences.Several measurement methods are available to determine torsional malalignment.While conventional X-ray or computed tomography would entail additional radiation exposure for the patient, and while magneti

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