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math.OC2026

Afterimage Slow Regions in First-Order Methods for Linear Conic Programming

Shucheng Kang, Heng Yang

First-order methods for linear conic programming often stall on long plateaus. Existing analyses characterize when during a run or on which problem instances slow convergence occur…

math.OC2026

Simplicial Regularizability of the Pseudo-Moment Cone and Carathéodory-Type Atomic Decomposition of Moment Matrices

Shucheng Kang, Heng Yang

We study the facial geometry of the homogeneous pseudo-moment cone \(Σ_{n,2d}^*\) and its implications for atomic decomposition of moment matrices. For fixed \(d \ge 2\), we show t…

math.OC2026

Local Second-Order Limit Dynamics of the Alternating Direction Method of Multipliers for Semidefinite Programming

Shucheng Kang, Heng Yang

The alternating direction method of multipliers (ADMM) is widely used for solving large-scale semidefinite programs (SDPs), yet on instances with multiple primal-dual optimal solut…

math.OC2025

Factorization-free Orthogonal Projection onto the Positive Semidefinite Cone with Composite Polynomial Filtering

Shucheng Kang, Haoyu Han, Antoine Groudiev +1

We propose a factorization-free method for orthogonal projection onto the positive semidefinite (PSD) cone, leveraging composite polynomial filtering. Inspired by recent advances i…

math.OC2025

Local Linear Convergence of the Alternating Direction Method of Multipliers for Semidefinite Programming under Strict Complementarity

Shucheng Kang, Xin Jiang, Heng Yang

We investigate the local linear convergence properties of the Alternating Direction Method of Multipliers (ADMM) when applied to Semidefinite Programming (SDP). A longstanding beli…

math.OC2024

Fast and Certifiable Trajectory Optimization

Shucheng Kang, Xiaoyang Xu, Jay Sarva +2

We propose semidefinite trajectory optimization (STROM), a framework that computes fast and certifiably optimal solutions for nonconvex trajectory optimization problems defined by…