Country
Banach Wasserstein GAN
So far the community has considered`2 as the underlying distance.
Dual Variational Generation for Low Shot Heterogeneous Face Recognition
Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He
Neural Information Processing Systems http://nips.cc/
Quality Aware Generative Adversarial Networks
KANCHARLA PARIMALA, Sumohana Channappayya
Alargenumber ofveryinteresting anduseful applications have emerged due to the ability of GANs to learn complex real-world distributions.
Efficient Online Portfolio with Logarithmic Regret
Haipeng Luo, Chen-Yu Wei, Kai Zheng
Neural Information Processing Systems http://nips.cc/
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
The number of features is comparable to the sample size and errors may be heavy-tailed.
Deep Active Learning with a Neural Architecture Search
Neural Information Processing Systems http://nips.cc/
Practical Deep Learning with Bayesian Principles
Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz E. Khan, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota
Figure 2: distributed calculation algorithmic Momentum Itiswell improv to Adam, where 1isthemomentumµin in Adaminit.xavier_normalin V methods, and AUR andissecond-best significantly and Adam Wealsosho7] in Figures itscalibration ImageNet, required Wealso different protocol 16,31,8,32] tocompare Wealsoborro16,30], sho reporting Ideally, we data.