|
Poster
|
Wed 14:30
|
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality
Taiji Suzuki
|
|
|
Poster
|
Wed 14:30
|
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
Vaishnavh Nagarajan · Zico Kolter
|
|
|
Poster
|
Thu 14:30
|
Amortized Bayesian Meta-Learning
Sachin Ravi · Alex Beatson
|
|
|
Poster
|
Wed 14:30
|
Critical Learning Periods in Deep Networks
Alessandro Achille · Matteo Rovere · Stefano Soatto
|
|
|
Poster
|
Wed 14:30
|
Aggregated Momentum: Stability Through Passive Damping
James Lucas · Shengyang Sun · Richard Zemel · Roger Grosse
|
|
|
Poster
|
Wed 9:00
|
Automatically Composing Representation Transformations as a Means for Generalization
Michael Chang · Abhishek Gupta · Sergey Levine · Thomas L Griffiths
|
|
|
Poster
|
Thu 14:30
|
Learning from Positive and Unlabeled Data with a Selection Bias
Masahiro Kato · Takeshi Teshima · Junya Honda
|
|
|
Poster
|
Tue 14:30
|
Towards the first adversarially robust neural network model on MNIST
Lukas Schott · Jonas Rauber · Matthias Bethge · Wieland Brendel
|
|
|
Poster
|
Thu 9:00
|
Learning Recurrent Binary/Ternary Weights
Arash Ardakani · Zhengyun Ji · Sean Smithson · Brett Meyer · Warren Gross
|
|
|
Poster
|
Wed 14:30
|
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Michael Lutter · Christian Ritter · Jan Peters
|
|
|
Poster
|
Wed 14:30
|
The role of over-parametrization in generalization of neural networks
Behnam Neyshabur · Zhiyuan Li · Srinadh Bhojanapalli · Yann LeCun · Nathan Srebro
|
|
|
Poster
|
Tue 9:00
|
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
Wieland Brendel · Matthias Bethge
|
|
