Frontiers of Deep Learning

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2019-09-26 14:11:34
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Robust Deep Learning Under Distribution Shift
50:19
Interpretability - now what?
47:38
Interpreting Deep Neural Networks (DNNs)
46:48
Provable Robustness Beyond Bound Propagation
47:56
Splitting Gradient Descent for Incremental Learning of Neural Architectures
51:46
Computation in Very Wide Neural Networks
48:40
Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets
45:12
A Primal-dual Analysis of Margin Maximization by Steepest Descent Methods
41:42
Size-free Generalization Bounds for Convolutional Neural Networks
34:34
1Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
46:39
A New Perspective on Adversarial Perturbations
48:49
Learning and Generalization in Over-parametrized Neural Networks, Going Beyond
49:42
From Classical Statistics to Modern Machine Learning
49:47
Benign Overfitting in Linear Prediction
47:40
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