Smoothed Analysis of the Simplex Method. - Daniel Dadush; Sophie Huiberts (Beyond the Worst-Case Analysis of Algorithms, 2020)

Simple Iterative Methods for Linear Optimization over Convex Sets. - Daniel Dadush; Christopher Hojny; Sophie Huiberts; Stefan Weltge (CoRR, 2020)

A Friendly Smoothed Analysis of the Simplex Method. - Daniel Dadush; Sophie Huiberts (SIAM J. Comput., 2020)

Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes. - Gilles Bonnet; Daniel Dadush; Uri Grupel; Sophie Huiberts; Galyna Livshyts (SoCG, 2022)

Prizes and Prejudice. - Sophie Huiberts (Bull. EATCS, 2022)

Upper and Lower Bounds on the Smoothed Complexity of the Simplex Method. - Sophie Huiberts; Yin Tat Lee; Xinzhi Zhang 002 (STOC, 2023)

On the integrality gap of binary integer programs with Gaussian data. - Sander Borst; Daniel Dadush; Sophie Huiberts; Samarth Tiwari (Math. Program., 2023)

A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. - Daniel Dadush; Sophie Huiberts; Bento Natura; László A. Végh (Math. Program., 2024)

A simple method for convex optimization in the oracle model. - Daniel Dadush; Christopher Hojny; Sophie Huiberts; Stefan Weltge (Math. Program., 2024)

A nearly optimal randomized algorithm for explorable heap selection. - Sander Borst; Daniel Dadush; Sophie Huiberts; Danish Kashaev (Math. Program., 2025)

Optimal Smoothed Analysis of the Simplex Method. - Eleon Bach; Sophie Huiberts (CoRR, 2025)

An unconditional lower bound for the active-set method in convex quadratic maximization. - Eleon Bach; Yann Disser; Sophie Huiberts; Nils Mosis (CoRR, 2025)