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quant-ph2025
Quantum Optimization via Gradient-Based Hamiltonian Descent
Jiaqi Leng, Bin Shi
With rapid advancements in machine learning, first-order algorithms have emerged as the backbone of modern optimization techniques, owing to their computational efficiency and low…
math.SP2025
On Pseudospectral Concentration for Rank-1 Sampling
Kuo Gai, Bin Shi
Pseudospectral analysis serves as a powerful tool in matrix computation and the study of both linear and nonlinear dynamical systems. Among various numerical strategies, random sam…
math.OC2025
A Family of Controllable Momentum Coefficients for Forward-Backward Accelerated Algorithms
Mingwei Fu, Bin Shi
Nesterov's accelerated gradient method (NAG) marks a pivotal advancement in gradient-based optimization, achieving faster convergence compared to the vanilla gradient descent metho…