| Abstract | We define a graph structure over predicates that represents entailment relations as directed edges, and use a global transitivity constraint on the graph to learn the optimal set of edges, by formulating the optimization problem as an Integer Linear Program. |
| Background | A Linear Program (LP) is an optimization problem , where a linear function is minimized (or maximized) under linear constraints. |
| Conclusion | We used Integer Linear Programming to solve the optimization problem , which is theoretically sound, and demonstrated empirically that this method outperforms local algorithms as well as a greedy optimization algorithm on the graph learning task. |
| Introduction | The optimization problem is formulated as an Integer Linear Program (ILP) and solved with an ILP solver. |