accelerated gradient methods 1asymptotic convergence rate 1hessian-driven dynamics 1lyapunov analysis 1strongly convex optimization 1
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math.OC2026
HNAG: An Accelerated Gradient Method with a Refined Asymptotic Rate for Strongly Convex Optimization
Long Chen, Zeyi Xu
The paper introduces two accelerated first‑order algorithms, HNAG⁺ and HNAG⁺⁺, for smooth strongly convex problems, achieving optimal global convergence and a refined asymptotic ra…
math.OC2026
Adaptive Accelerated Gradient Descent Methods for Convex Optimization
Zeyi Xu, Long Chen
This work proposes AGD, a novel adaptive accelerated gradient descent method for convex and composite optimization. Smoothness and convexity constants are updated via Lyapunov…
math.OC2026
Accelerated Mirror Descent Method through Variable and Operator Splitting
Long Chen, Hao Luo, Jingrong Wei +2
Mirror descent uses the mirror function to encode geometry and constraints, improving convergence while preserving feasibility. Accelerated Mirror Descent Methods (Acc-MD) are deri…