Predicting Neural Network Accuracy from Weights

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In this paper (Unterthiner et al., 2020) showed empirically that we can predict the generalization gap of a neural network by only looking at its weights. In this work, they released a dataset of 120k convolutional neural networks trained...

Predicting The Generalization Gap In Deep Networks With Margin Distributions

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In this paper (Jiang et al., 2018), they discuss a method that can predict the generalization gap from trained deep neural networks. The authors used marginal distribution information from input training set as a feature vector used by an...

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.