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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…
math.OC2025
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…