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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…
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…
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…