Introduction to Mixed Integer Programming

Mixed-Integer programming are used to solve optimization problems with discrete decision variables. Hence, its feasible region is a set of disconnected integer points and gradient based algorithms cannot be directly applied.

Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming

In this research, we attempt to understand the neural model architecture by computing an importance score to neurons. The computed importance score can be used to prune the model or to understand which features are more meaningful to the trained ANN (artificial neural...

Explaining PackNet Adding Multiple Tasks to a Single Network by Iterative Pruning

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In this paper (Mallya & Lazebnik, 2017), they discuss a method for adding and supporting multiple tasks in a single architecture without having to worry about catastrophic forgetting . They show in this paper that three fine-grained classification tasks can be added...