
Predicting Neural Network Accuracy from Weights
Paper Review ·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 on different datasets.
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Predicting The Generalization Gap In Deep Networks With Margin Distributions
Paper Review ·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 estimator to get...

Introduction to Mixed Integer Programming
Tutorials ·MixedInteger 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.