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Quantum policy gradient algorithms
Understanding the power and limitations of quantum access to data in machine learning tasks is primordial to assess the potential of quantum computing in artificial intelligence.
A Sublinear-Time Quantum Algorithm for Approximating Partition Functions
We present a novel quantum algorithm for estimating Gibbs partition functions in sublinear time with respect to the logarithm of the size of the state space.
Near-Optimal Quantum Algorithms for Multivariate Mean Estimation
We propose the first near-optimal quantum algorithm for estimating in Euclidean norm the mean of a vector-valued random variable with finite mean and covariance.
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