NIPS is a single-track machine learning and computational neuroscience conference that includes invited talks, demonstrations and oral and poster presentations of refereed papers.

The Marginal Value of Adaptive Gradient Methods in Machine Learning

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

Learning to Compose Domain-Specific Transformations for Data Augmentation.

Neural Information Processing Systems Conference - 2017 via Local dblp

Keywords:

Neural Information Processing Systems Conference - 2017 via Local dblp

Keywords:

The Reversible Residual Network: Backpropagation Without Storing Activations.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

Keywords:

Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

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Prototypical Networks for Few-shot Learning

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, stat.ML

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, stat.ML

Learned in Translation: Contextualized Word Vectors

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CL, cs.AI, cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CL, cs.AI, cs.LG

Neural Discrete Representation Learning

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG

Deep Reinforcement Learning from Human Preferences.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

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Dynamic Routing Between Capsules.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

Keywords:

Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

Keywords:

Self-Normalizing Neural Networks

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, stat.ML

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, stat.ML

A Regularized Framework for Sparse and Structured Neural Attention.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

Keywords:

Triangle Generative Adversarial Networks

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, stat.ML

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, stat.ML

Fader Networks: Manipulating Images by Sliding Attributes

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

Bayesian Compression for Deep Learning

arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG

A simple neural network module for relational reasoning

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CL, cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CL, cs.LG

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