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20242026
most citedOn Distributionally Robust Multistage Convex Optimization: New Algorithms and Complexity Analysis

2 citations · 2 across the 1 of their papers we have counts for

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6 papers

math.OC20262 cited

On Distributionally Robust Multistage Convex Optimization: New Algorithms and Complexity Analysis

Shixuan Zhang, Xu Andy Sun

This paper presents an algorithmic study and complexity analysis for solving distributionally robust multistage convex optimization (DR-MCO) problems. Our main contribution is a no…

math.OC2025

On Distributionally Robust Multistage Convex Optimization: Data-driven Models and Performance

Shixuan Zhang, Xu Andy Sun

This paper presents a novel algorithmic study with extensive numerical experiments of distributionally robust multistage convex optimization (DR-MCO). Following the previous work o…

math.OC2025

Moment Relaxations for Data-Driven Wasserstein Distributionally Robust Optimization

Shixuan Zhang, Suhan Zhong

We propose moment relaxations for data-driven Wasserstein distributionally robust optimization problems. Conditions are identified to ensure asymptotic consistency of such relaxati…

math.NT2025

Semigroups of Integer Points in Convex Cones

Grigoriy Blekherman, Jesús A. De Loera, Luze Xu +1

We study the question whether the affine semigroup of integer points in a convex cone can be finitely generated up to symmetries of the cone. We establish general properties of fin…

math.OC2025

Integer Points in Arbitrary Convex Cones: The Case of the PSD and SOC Cones

Jesús A. De Loera, Brittney Marsters, Luze Xu +1

We investigate the semigroup of integer points inside a convex cone. We extend classical results in integer linear programming to integer conic programming. We show that the semigr…

math.OC2024

Spurious local minima in nonconvex sum-of-squares optimization

Grigoriy Blekherman, Rainer Sinn, Mauricio Velasco +1

We study spurious second-order stationary points and local minima in a nonconvex low-rank formulation of sum-of-squares optimization on a real variety . We reformulate the probl…