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HNAG: An Accelerated Gradient Method with a Refined Asymptotic Rate for Strongly Convex Optimization
Long Chen, Zeyi Xu
Two accelerated first-order methods, HNAG and HNAG, are introduced for smooth strongly convex optimization. They are derived from the Hessian-driven Nesterov Accelerated…
Optimal quantum sampling on distributed databases
Longyun Chen, Jingcheng Liu, Penghui Yao
Quantum sampling, a fundamental subroutine in numerous quantum algorithms, involves encoding a given probability distribution in the amplitudes of a pure state. Given the hefty cos…
Optimal quantum metrology under energy constraints
Longyun Chen, Yuxiang Yang
The traditional framework of quantum metrology commonly assumes unlimited access to resources, overlooking resource constraints in realistic scenarios. As such, the optimal strateg…
Tuning-Free Structured Sparse PCA via Deep Unfolding Networks
Long Chen, Xianchao Xiu
Sparse principal component analysis (PCA) is a well-established dimensionality reduction technique that is often used for unsupervised feature selection (UFS). However, determining…