activity
20242026
collaborators

8 papers

math.MG2026

A centerpoint theorem for three planar convex bodies

Hongyu Cheng, Amitabh Basu

For planar convex bodies satisfying , we prove that the union of the three slices , , co…

cs.LG2026

Sample Complexity of Stochastic Optimization with Integer Variables

Hongyu Cheng, Yinghao Zheng, Marco Molinaro +1

We establish sample complexity results for stochastic optimization over the integers, especially with a view to understand the complexity with respect to the corresponding continuo…

math.OC2026

Linear Threshold for Oertel's Conjecture on the Mixed-Integer Volume

Hongyu Cheng, Amitabh Basu

Grünbaum's inequality guarantees that the centroid of a convex body has halfspace depth at least : every halfspace containing the centroid captures at least a fraction o…

math.OC2026

Theoretical Challenges in Learning for Branch-and-Cut

Hongyu Cheng, Amitabh Basu

Machine learning is increasingly used to guide branch-and-cut (B&C) for mixed-integer linear programming by learning score-based policies for selecting branching variables and cutt…

math.OC2025

Identifying faulty edges in resistive electrical networks

Barbara Fiedorowicz, Amitabh Basu

Given a resistive electrical network, we would like to determine whether all the resistances (edges) in the network are working, and if not, identify which edge (or edges) are faul…

cs.LG2025

Generalization Guarantees for Learning Branch-and-Cut Policies in Integer Programming

Hongyu Cheng, Amitabh Basu

Mixed-integer programming (MIP) provides a powerful framework for optimization problems, with Branch-and-Cut (B&C) being the predominant algorithm in state-of-the-art solvers. The…

math.OC2024

Learning Cut Generating Functions for Integer Programming

Hongyu Cheng, Amitabh Basu

The branch-and-cut algorithm is the method of choice to solve large scale integer programming problems in practice. A key ingredient of branch-and-cut is the use of cutting planes…

cs.LG2024

Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut

Hongyu Cheng, Sammy Khalife, Barbara Fiedorowicz +1

Data-driven algorithm design is a paradigm that uses statistical and machine learning techniques to select from a class of algorithms for a computational problem an algorithm that…