Solving mixed integer classification problems by decomposition

By Paul A. Rubin. 1997

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Cynthia Rudin
2. Berk Ustun
3. Tong Wang
4. Matteo Fischetti
5. Gianni Codato
6. Nadia Burkart
7. Ş. Ertekin
8. Alexey Ignatiev

Citations in the corpus

• Methods and Models for Interpretable Linear Classification (2014, methodology): “This is a Big-M formulation for the 0–1 loss that depends on scalar parameters γ and Mi (see e.g. Rubin 97).”
• Combinatorial Benders' Cuts for Mixed-Integer Linear Programming (2006, methodology): “(In [31] a slightly different MIP model is used, involving also a real-valued variables in the objective; this model can easily be transformed into the one we use in the present study.”