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Year Published

391 Results

August 6, 2017

Efficient Softmax Approximation for GPUs

International Conference on Machine Learning (ICML)

We propose an approximate strategy to efficiently train neural network based language models over very large vocabularies.

By: Edouard Grave, Armand Joulin, Moustapha Cisse, David Grangier, Hervé Jégou
August 6, 2017

Convolutional Sequence to Sequence Learning

International Conference on Machine Learning (ICML)

We introduce an architecture based entirely on convolutional neural networks.

By: Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
August 6, 2017

Unsupervised Learning by Predicting Noise

International Conference on Machine Learning (ICML)

Convolutional neural networks provide visual features that perform well in many computer vision applications. However, training these networks requires large amounts of supervision; this paper introduces a generic framework to train such networks, end-to-end, with no supervision. We propose to fix a set of target representations, called Noise As Targets (NAT), and to constrain the deep features to align to them.

By: Piotr Bojanowski, Armand Joulin
August 6, 2017

Wasserstein Generative Adversarial Networks

International Conference on Machine Learning (ICML)

We introduce a new algorithm named WGAN, an alternative to traditional GAN training. In this new model, we show that we can improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches.

By: Martin Arjovsky, Soumith Chintala, Leon Bottou
July 31, 2017

Enriching Word Vectors with Subword Information

TACL, Association for Computational Linguistics (ACL 2017)

In this paper, we propose a new approach based on the skipgram model, where each word is represented as a bag of character n-grams.

By: Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov
July 31, 2017

Learning Multilingual Joint Sentence Embeddings with Neural Machine Translation

ACL workshop on Representation Learning for NLP (ACL)

In this paper, we use the framework of neural machine translation to learn joint sentence representations across six very different languages. Our aim is that a representation which is independent of the language, is likely to capture the underlying semantics.

By: Holger Schwenk, Matthijs Douze
July 30, 2017

Focal Surface Displays

SIGGRAPH 2017

We introduce focal surface displays to meet the challenge of vergence-accommodation conflict, augmenting conventional HMDs with a phase-only spatial light modulator (SLM) placed between the display screen and viewing optics. This SLM acts as a dynamic freeform lens, shaping synthesized focal surfaces to conform to the virtual scene geometry.

By: Nathan Matsuda, Alexander Fix, Douglas Lanman
Areas: AR/VR
July 30, 2017

Low-Cost 360 Stereo Photography and Video Capture

SIGGRAPH 2017

In this work, we describe a method that takes images from two 360◦ spherical cameras and synthesizes an omni-directional stereo panorama with stereo in all directions. Our proposed method has a lower equipment cost than camera-ring alternatives, can be assembled with currently available off-the-shelf equipment, and is relatively small and light-weight compared to the alternatives.

By: Kevin Matzen, Michael Cohen, Bryce Evans, Johannes Kopf, Richard Szeliski
July 30, 2017

Reading Wikipedia to Answer Open-Domain Questions

Association for Computational Linguistics (ACL 2017)

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article.

By: Danqi Chen, Adam Fisch, Jason Weston, Antoine Bordes
July 30, 2017

Automatically Generating Rhythmic Verse with Neural Networks

Association for Computational Linguistics (ACL 2017)

We propose two novel methodologies for the automatic generation of rhythmic poetry in a variety of forms.

By: Jack Hopkins, Douwe Kiela