Publications

Papers Under Review

• Matthias Köppe, Moises Reyes Rivas, and Luze Xu. (2024). Determining Sharp Proximity Bounds For Low Row Rank and ∆-Modularity. Accepted in 2024 INFORMS Optimization Society Conference.

• Jesús De Loera, Brittney Marsters, Luze Xu, Shixuan Zhang. (2023). Integer points in arbitrary convex cones: the case of the PSD and SOC cones. A conference version is accepted in the 25th Conference on Integer Programming and Combinatorial Optimization (IPCO) 2024.

• Joseph Paat, Zach Walsh, Luze Xu. (2023). Extended formulations for a class of polyhedra with bimodular cographic constraint matrices.

• Gabriel Ponte, Marcia Fampa, Jon Lee, Luze Xu. (2024). Good and fast row-sparse ah-symmetric reflexive generalized inverses.

Journal Papers

• Luze Xu, Jon Lee. Gaining or losing perspective for convex multivariate functions on box domains. Mathematical Programming, 2024.

• Gabriel Ponte, Marcia Fampa, Jon Lee, Luze Xu. On computing sparse generalized inverses. Operations Research Letters, 52:107058, 2024.    

• Luze Xu, Jon Lee.  Gaining or losing perspective for convex multivariate functions on a simplex. Journal of Global Optimization, 2024.   

• Joseph Paat, Ingo Stallknecht, Zach Walsh, Luze Xu. On the column number and forbidden sumatrices of Delta-modular matrices. SIAM Journal on Discrete Mathematics, 2024.

• Jon Lee, Daphne Skipper, Emily Speakman, Luze Xu.  Gaining or losing perspective for piecewise-linear under-estimators of convex univariate functions. Journal version. Journal of Optimization Theory and Applications, 196:1-35, 2023. 

  • Earlier version in: Graphs and Combinatorial Optimization: from Theory to Applications, CTW 2020, Claudio Gentile, Giuseppe Stecca and Paolo Ventura, editors. AIRO Springer Series, Volume 5, pp 349-360, 2021.

• Jon Lee, Joseph Paat, Ingo Stallknecht, Luze Xu. Polynomial upper bounds on the number of differing columns of Δ-modular integer programs. Mathematics of Operations Research, 2022. 

• Luze Xu, Marcia Fampa, Jon Lee, Gabriel Ponte.  Approximate 1-norm minimization and minimum-rank structured sparsity for various generalized inverses via local search. SIAM Journal on Optimization, 31(3):1722-1747, 2021.  

• Marcia Fampa, Jon Lee, Gabriel Ponte, Luze Xu. Experimental analysis of local search for sparse reflexive generalized inverses. Journal of Global Optimization, 81:1057-1093, 2021. 

• Luze Xu, Jon Lee, Daphne Skipper. More virtuous smoothing. SIAM Journal on Optimization, 29(2):1240–1259, 2019.

Referred Conference Proceedings & Referred Book Chapters

• Luze Xu, Marcia Fampa, Jon Lee. 1-norm minimization and minimum-rank structured sparsity for symmetric and ah-symmetric generalized inverses: rank one and two. To appear in: Fields Institute Communications Series volume on Data Science and Optimization (Deza, Gupta, Pokutta, eds.). 

• Jon Lee, Joseph Paat, Ingo Stallknecht, Luze Xu. (2020). Improving proximity bounds using sparsity.  ISCO 2020, 115-127. Lecture Notes in Computer Science, Springer. 

• Luze Xu, Jon Lee. (2020). On proximity for k-regular mixed-integer linear optimization. In: WCGO 2019: Optimization of Complex Systems: Theory, Models, Algorithms and Applications, 2020, Le Hoai An Thi, Hoai Minh Le, Tao Pham Dinh, eds. pp. 438-447.