On the sample complexity of quantum Boltzmann machine learning

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 mug polynomial size of the data set.By using the relative entropy as a loss function, this

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Emergence of rhythmic chunking in complex stepping of mice

Summary: Motor chunking is important for motor execution, allowing atomization and efficiency of movement sequences.However, it remains unclear why and how chunks contribute to motor execution.To analyze the structure of naturally occurring chunks, we trained mice to run in a complex series of steps Glasschliffarmbänder and identified the formatio

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