1 citations · 1 across the 8 of their papers we have counts for
9 papers
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…
Bias-Variance Trade-off for Clipped Stochastic First-Order Methods: From Bounded Variance to Infinite Mean
Chuan He
Stochastic optimization is fundamental to modern machine learning. Recent research has extended the study of stochastic first-order methods (SFOMs) from light-tailed to heavy-taile…
Accelerated stochastic first-order method for convex optimization under heavy-tailed noise
Chuan He, Zhaosong Lu, Bowen Li
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…
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…
Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian
Chuan He, Heng Huang, Zhaosong Lu
In this paper we consider a nonconvex unconstrained optimization problem minimizing a twice differentiable objective function with Hölder continuous Hessian. Specifically, we first…
A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition
Masaru Ito, Zhaosong Lu, Chuan He
In this paper we consider a composite optimization problem that minimizes the sum of a weakly smooth function and a convex function with either a bounded domain or a uniformly conv…
A Newton-CG based augmented Lagrangian method for finding a second-order stationary point of nonconvex equality constrained optimization with complexity guarantees
Chuan He, Zhaosong Lu, Ting Kei Pong
In this paper we consider finding a second-order stationary point (SOSP) of nonconvex equality constrained optimization when a nearly feasible point is known. In particular, we fir…
A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization
Chuan He, Heng Huang, Zhaosong Lu
In this paper we consider finding an approximate second-order stationary point (SOSP) of general nonconvex conic optimization that minimizes a twice differentiable function subject…
A Newton-CG based barrier method for finding a second-order stationary point of nonconvex conic optimization with complexity guarantees
Chuan He, Zhaosong Lu
In this paper we consider finding an approximate second-order stationary point (SOSP) of nonconvex conic optimization that minimizes a twice differentiable function over the inters…