Sophie Huiberts

According to our database, Sophie Huiberts authored at least 13 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Beyond Smoothed Analysis: Analyzing the Simplex Method By-the-Book.

Eleon Bach, Alexander E. Black, Sophie Huiberts, Sean Kafer

Proceedings of the 58th Annual ACM Symposium on Theory of Computing, 2026

An Unconditional Lower Bound for the Active-Set Method in Convex Quadratic Maximization.

Eleon Bach, Yann Disser, Sophie Huiberts, Nils Mosis

Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms, 2026

2025

Optimal Smoothed Analysis of the Simplex Method.

Eleon Bach, Sophie Huiberts

Proceedings of the 66th IEEE Annual Symposium on Foundations of Computer Science, 2025

2023

Upper and Lower Bounds on the Smoothed Complexity of the Simplex Method.

Sophie Huiberts, Yin Tat Lee, Xinzhi Zhang

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

A Nearly Optimal Randomized Algorithm for Explorable Heap Selection.

Sander Borst, Daniel Dadush, Sophie Huiberts, Danish Kashaev

Proceedings of the Integer Programming and Combinatorial Optimization, 2023

2022

Prizes and Prejudice.

Sophie Huiberts

Bull. EATCS, 2022

A Simple Method for Convex Optimization in the Oracle Model.

Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge

Proceedings of the Integer Programming and Combinatorial Optimization, 2022

Asymptotic Bounds on the Combinatorial Diameter of Random Polytopes.

Gilles Bonnet, Daniel Dadush, Uri Grupel, Sophie Huiberts, Galyna V. Livshyts

Proceedings of the 38th International Symposium on Computational Geometry, 2022

2021

On the Integrality Gap of Binary Integer Programs with Gaussian Data.

Sander Borst, Daniel Dadush, Sophie Huiberts, Samarth Tiwari

Proceedings of the Integer Programming and Combinatorial Optimization, 2021

2020

Simple Iterative Methods for Linear Optimization over Convex Sets.

Daniel Dadush, Christopher Hojny, Sophie Huiberts, Stefan Weltge

CoRR, 2020

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

Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

Smoothed Analysis of the Simplex Method.

Daniel Dadush, Sophie Huiberts

Proceedings of the Beyond the Worst-Case Analysis of Algorithms, 2020

2018

A friendly smoothed analysis of the simplex method.

Daniel Dadush, Sophie Huiberts

Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018