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...

Stabilizing GAN training With Random Projections

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In this paper (Neyshabur et al., 2017), They introduced a framework to stabilize the GAN training by using multiple projections with fixed filters of each input image to a different discriminator. Training GAN models is unstable in high dimensional space and some...