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Poster
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Tue 9:00
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Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
Wenda Zhou · Victor Veitch · Morgane Austern · Ryan P Adams · Peter Orbanz
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Poster
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Wed 9:00
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Automatically Composing Representation Transformations as a Means for Generalization
Michael Chang · Abhishek Gupta · Sergey Levine · Thomas L Griffiths
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Poster
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Wed 14:30
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Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
Vaishnavh Nagarajan · Zico Kolter
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Poster
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Wed 14:30
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The role of over-parametrization in generalization of neural networks
Behnam Neyshabur · Zhiyuan Li · Srinadh Bhojanapalli · Yann LeCun · Nathan Srebro
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Poster
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Wed 14:30
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An analytic theory of generalization dynamics and transfer learning in deep linear networks
Andrew Lampinen · Surya Ganguli
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Poster
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Wed 14:30
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Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality
Taiji Suzuki
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Poster
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Tue 14:30
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Improving the Generalization of Adversarial Training with Domain Adaptation
Chuanbiao Song · Kun He · Liwei Wang · John E Hopcroft
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Poster
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Wed 14:30
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Regularized Learning for Domain Adaptation under Label Shifts
Kamyar Azizzadenesheli · Anqi Liu · Fanny Yang · Anima Anandkumar
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Poster
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Thu 14:30
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Deep learning generalizes because the parameter-function map is biased towards simple functions
Guillermo Valle-Perez · Chico Q. Camargo · Ard Louis
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Poster
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Wed 14:30
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Predicting the Generalization Gap in Deep Networks with Margin Distributions
YiDing Jiang · Dilip Krishnan · Hossein Mobahi · Samy Bengio
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Poster
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Wed 9:00
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An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva · Alessandro Sordoni · Remi Combes · Adam Trischler · Yoshua Bengio · Geoffrey Gordon
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Poster
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Wed 14:30
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On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
Stanislaw Jastrzebski · Zachary Kenton · Nicolas Ballas · Asja Fischer · Yoshua Bengio · Amos Storkey
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