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20232026
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math.OC2026

Randomized Quasi-Gauss--Newton Methods for Solving General Nonlinear Equations

Chengchang Liu, Luo Luo

This paper considers the local convergence for solving general nonlinear equations. We establish randomized quasi-Gauss--Newton methods based on the approximation of the Gram matri…

math.OC2026

Halpern Iteration Achieves th-Order Oracle Complexity for Monotone Variational Inequalities

Lesi Chen, Xinliang Zhang, Hengyu Wang +3

We study second- and higher-order methods for solving smooth monotone variational inequalities (MVI). Monteiro and Svaiter (SIAM J. Optim., 2012) showed that a second-order method,…

math.OC2026

Optimal Convex Optimization with Inexact Second-Order Oracles

Lesi Chen, Chengchang Liu, Luo Luo +2

In this paper, we present a novel second-order method called Accelerated Inexact Newton Extragradient (AINE) for convex optimization using -inexact Hessians. We show that AINE c…

math.OC2026

Stochastic Non-Smooth Non-Convex Optimization with Decision-Dependent Distributions

Chengchang Liu, Zongqi Wan, Haishan Ye +1

We study stochastic zeroth-order optimization with decision-dependent distributions, where the sampling law depends on the current decision and only noisy function values are avail…

math.OC2026

Second-Order Bilevel Optimization with Accelerated Convergence Rates

Sheng Yang, Chengchang Liu, Lesi Chen +1

This paper studies second-order methods for nonconvex-strongly-convex bilevel optimization. We propose a novel fully second-order bilevel approximation method (FSBA) that achieves…

math.OC2026

Solving Convex-Concave Problems with th-Order Oracle Complexity

Lesi Chen, Xinliang Zhang, Chengchang Liu +3

When the objective has Lipschitz continuous th-order derivatives, it is known that convex-concave minimax problems can be solved with th-order ora…