|DATE||November 23 (Mon), 2020|
|SPEAKER||de Mello Koch, Robert|
|INSTITUTE||University of Witwatersrand, 남아프리카공화국|
|TITLE||Why deep networks generalize|
Training a deep network involves applying an algorithm which fixes the parameters of the network. The performance of the trained deep network is evaluated by studying the trained network's performance on unseen test data. The difference between how the network performs on the training data and on unseen data defines a generalization error. Networks that perform as well on unseen data as they did on training data, have a small generalization error.