30 мая 2018 г. · In this work we suggest a novel complexity measure based on unit-wise capacities resulting in a tighter generalization bound for two layer ReLU networks.

20 дек. 2018 г. · We suggest a generalization bound that could partly explain the improvement in generalization with over-parametrization. Understanding Over-parameterization in Generative ... Role of Over-Parameterization in Generalization of 3-layer ... Towards Understanding Generalization of Graph Neural ... Understanding How Over-Parametrization Leads to Acceleration Другие результаты с сайта openreview.net

This work provides theoretical and empirical evidence that, in certain cases, overparameterized convolutional networks generalize better than small networks.

We empirically investigate the role of over-parametrization in generalization of neural networks on 3 different datasets (MNIST, CIFAR10 and SVHN), and show ...

12 сент. 2024 г. · In this work we suggest a novel complexity measure based on unit-wise capacities resulting in a tighter generalization bound for two layer ReLU ...

What are the reasons suggested by the authors that could explain why over-parameterization improves generalization error? ○ Lower difference between initial and ...

11 дек. 2019 г. · Towards Understanding the Role of. Over-Parametrization in Generalization of. Neural Networks. Behnam Neyshabur, Zhiyuan Li, Srinadh ...

11 дек. 2019 г. · In this talk I presented and discussed a paper dealing with generalization bounds for neural networks. You can look at the slides here. Share on.

Traditional thought: NNs are prone to overfitting to training data → require regularization etc. Fact: increasing model size improves generalization error (even ...

1 янв. 2019 г. · In this work we suggest a novel complexity measure based on unit-wise capacities resulting in a tighter generalization bound for two layer ReLU ...