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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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Wed 14:30
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Critical Learning Periods in Deep Networks
Alessandro Achille · Matteo Rovere · Stefano Soatto
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Poster
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Thu 9:00
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Learning Recurrent Binary/Ternary Weights
Arash Ardakani · Zhengyun Ji · Sean Smithson · Brett Meyer · Warren Gross
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Poster
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Wed 14:30
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Aggregated Momentum: Stability Through Passive Damping
James Lucas · Shengyang Sun · Richard Zemel · Roger Grosse
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Poster
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Wed 14:30
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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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Thu 14:30
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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
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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 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 9:00
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Optimal Completion Distillation for Sequence Learning
Sara Sabour · William Chan · Mohammad Norouzi
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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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Quasi-hyperbolic momentum and Adam for deep learning
Jerry Ma · Denis Yarats
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Poster
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Wed 9:00
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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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