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Multi-arm bandit (MAB) and stochastic linear bandit (SLB) are important models in reinforcement learning, and it is well-known that classical algorithms for bandits with time horizon $T$ suffer $\Omega(\sqrt{T})$ regret.
Quantum supremacy using a programmable superconducting processor
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Random generation of combinatorial structures from a uniform distribution
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