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20132019
most citedTensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

9.7k citations · 16.8k across the 8 of their papers we have counts for

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Showing 2016Show all

5 papers · 1 filter

cs.CL2016★ 109 cited

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

Melvin Johnson, Mike Schuster, Quoc V. Le +9

We propose a simple solution to use a single Neural Machine Translation (NMT) model to translate between multiple languages. Our solution requires no change in the model architectu…

cs.CL2016★ 5.7k cited

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Yonghui Wu, Mike Schuster, Zhifeng Chen +28

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based tr…

cs.LG2016★ 88 cited

Reward Augmented Maximum Likelihood for Neural Structured Prediction

Mohammad Norouzi, Samy Bengio, Zhifeng Chen +4

A key problem in structured output prediction is direct optimization of the task reward function that matters for test evaluation. This paper presents a simple and computationally…

cs.DC2016★ 9.7k cited

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham +37

TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…

cs.CL2016★ 883 cited

Exploring the Limits of Language Modeling

Rafal Jozefowicz, Oriol Vinyals, Mike Schuster +2

In this work we explore recent advances in Recurrent Neural Networks for large scale Language Modeling, a task central to language understanding. We extend current models to deal w…