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114 Results
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Poster
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Wed 9:00 |
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 |
Critical Learning Periods in Deep Networks Alessandro Achille · Matteo Rovere · Stefano Soatto |
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Poster
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Wed 14:30 |
Aggregated Momentum: Stability Through Passive Damping James Lucas · Shengyang Sun · Richard Zemel · Roger Grosse |
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Poster
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Thu 14:30 |
Learning from Positive and Unlabeled Data with a Selection Bias Masahiro Kato · Takeshi Teshima · Junya Honda |
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Poster
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Tue 14:30 |
Towards the first adversarially robust neural network model on MNIST Lukas Schott · Jonas Rauber · Matthias Bethge · Wieland Brendel |
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Poster
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Wed 14:30 |
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning Michael Lutter · Christian Ritter · Jan Peters |
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Poster
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Wed 14:30 |
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 |
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 9:00 |
Optimal Completion Distillation for Sequence Learning Sara Sabour · William Chan · Mohammad Norouzi |
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Poster
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Wed 9:00 |
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning Sirui Xie · Junning Huang · Lanxin Lei · Chunxiao Liu · Zheng Ma · Wei Zhang · Liang Lin |
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Poster
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Tue 9:00 |
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet Wieland Brendel · Matthias Bethge |
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Poster
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Wed 14:30 |
Quasi-hyperbolic momentum and Adam for deep learning Jerry Ma · Denis Yarats |