works on

From the 1 of 10 linked papers with an AI index.

most citedA Robust EDM Optimization Approach for 3D Single-Source Localization with Angle and Range Measurements

1 citations · 1 across the 1 of their papers we have counts for

collaborators

10 papers

eess.SP20261 cited

A Robust EDM Optimization Approach for 3D Single-Source Localization with Angle and Range Measurements

Mingyu Zhao, Qingna Li, Hou-Duo Qi

The paper proposes a robust Euclidean distance matrix optimization method that jointly uses range and angle data with an L1-norm criterion to improve 3D single-source localization…

math.OC2026

On Constraint Qualifications for MPECs with Applications to Bilevel Hyperparameter Optimization for Machine Learning

Jiani Li, Qingna Li, Alain Zemkoho

Constraint qualifications for a Mathematical Program with Equilibrium Constraints (MPEC) are essential for analyzing stationarity properties and establishing convergence results. I…

cs.LG2026

TrasMuon: Trust-Region Adaptive Scaling for Orthogonalized Momentum Optimizers

Peng Cheng, Jiucheng Zang, Qingnan Li +6

Muon-style optimizers leverage Newton-Schulz (NS) iterations to orthogonalize updates, yielding update geometries that often outperform Adam-series methods. However, this orthogona…

math.NA2026

Fast Algorithms for Optimal Damping in Mechanical Systems

Qingna Li, Françoise Tisseur

Optimal damping aims at determining a vector of damping coefficients that maximizes the decay rate of a mechanical system's response. This problem can be formulated as the min…

math.OC2025

Modified Block Newton Algorithm for -Regularized Optimization

Yuge Ye, Qingna Li

In this paper, we propose a globally convergent Newton type method to solve regularized sparse optimization problem. In fact, a line search strategy is applied to the Newt…

math.OC2025

Proximal Iterative Hard Thresholding Algorithm for Sparse Group -Regularized Optimization with Box Constraint

Yuge Ye, Qingna Li

This paper investigates a general class of problems in which a lower bounded smooth convex function incorporating and regularization is minimized over a box…