Navid Ghadermarzy

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We investigate whether quantum annealers with select chip layouts can outperform classical computers in reinforcement learning tasks. We associate a transverse field Ising spin Hamiltonian with a layout of qubits similar to that of a deep Boltzmann machine (DBM) and use simulated quantum annealing (SQA) to numerically simulate quantum sampling from this(More)
In this paper we address the recovery conditions of weighted`p minimization for signal reconstruction from compressed sensing measurements when partial support information is available. We show that weighted`p minimization with H < p < I is stable and robust under weaker sufficient conditions compared to weighted`1 minimization. Moreover, the sufficient(More)
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