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math.OC2026
Adaptive Newton-CG methods with global and local analysis for unconstrained optimization with Hölder continuous Hessian
Ziyang Zeng, Junyu Zhang, Chuan He
In this paper, we study Newton-conjugate gradient (Newton-CG) methods for minimizing a nonconvex function whose Hessian is -Hölder continuous with modulus and…
math.OC2025
Accelerated stochastic first-order method for convex optimization under heavy-tailed noise
Chuan He, Zhaosong Lu
We study convex composite optimization problems, where the objective function is given by the sum of a prox-friendly function and a convex function whose subgradients are estimated…
math.OC2025
Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise
Chuan He, Zhaosong Lu, Defeng Sun +1
In this paper, we propose practical normalized stochastic first-order methods with Polyak momentum, multi-extrapolated momentum, and recursive momentum for solving unconstrained op…