Matthieu Devin
Matthieu Devin co-wrote papers on large-scale deep learning and on the TensorFlow system. In 2012, they co-wrote a NIPS paper on distributed deep networks and a paper on building high-level features through unsupervised learning. In 2013 they also co-wrote a paper on multiframe deep neural networks for acoustic modeling, published at ICASSP. Their name also appears among the authors of the 2016 OSDI paper describing TensorFlow, a large-scale machine learning system. ICML gave an honorable mention in its 2022 Test of Time awards to the 2012 unsupervised learning paper they co-wrote.
Timeline
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2012
A distributed deep networks paper
They co-write the NIPS 2012 paper 'Large Scale Distributed Deep Networks' with Jeffrey Dean and Andrew Ng.
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2012
Building high-level features
With Quoc Le and Andrew Ng, they co-write 'Building high-level features using large scale unsupervised learning', a 2012 paper.
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2013
Multiframe acoustic modeling
Vincent Vanhoucke and Georg Heigold join them on 'Multiframe Deep Neural Networks for Acoustic Modeling', published at ICASSP in 2013.
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2016
The TensorFlow system paper
They co-author 'TensorFlow: A System for Large-Scale Machine Learning' alongside Martín Abadi and Jeffrey Dean, published at OSDI in 2016.
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2022
A Test of Time honorable mention
In its 2022 awards, ICML gives a Test of Time honorable mention to 'Building high-level features using large scale unsupervised learning', a paper they co-wrote.
Sources and credits
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- Large Scale Distributed Deep Networks
- Building high-level features using large scale unsupervised learning
- [1112.6209] Building high-level features using large scale unsupervised learning
- Multiframe Deep Neural Networks for Acoustic Modeling
- TensorFlow: A system for large-scale machine learning
- TensorFlow: A System for Large-Scale Machine Learning | USENIX
- ICML 2022 Awards