PhD student in Machine Learning and Operations Research at CERMICS, Ecole des Ponts.
We present InferOpt.jl, a generic package for combining combinatorial optimization algorithms with machine learning models. It has two purposes:
- Increasing the expressivity of learning models thanks to new types of structured layers.
- Increasing the efficiency of optimization algorithms thanks to an additional inference step.
Our library provides wrappers for several state-of-the-art methods in order to make them compatible with Julia's automatic differentiation ecosystem.