4 papers · 1 filter
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…
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…
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…
Neural networks with linear threshold activations: structure and algorithms
Sammy Khalife, Hongyu Cheng, Amitabh Basu
In this article we present new results on neural networks with linear threshold activation functions. We precisely characterize the class of functions that are representable by suc…