Marc'Aurelio Ranzato

Affiliations:
  • DeepMind, London, UK
  • Facebook AI Research, New York City, NY, USA
  • Google, Maintain View, CA, USA
  • New York University, New York City, NY, USA (PhD 2009)


According to our database1, Marc'Aurelio Ranzato authored at least 87 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Online presence:

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Bibliography

2024
Asynchronous Local-SGD Training for Language Modeling.
CoRR, 2024

2023
DiLoCo: Distributed Low-Communication Training of Language Models.
CoRR, 2023

Towards Robust and Efficient Continual Language Learning.
CoRR, 2023

Towards Compute-Optimal Transfer Learning.
CoRR, 2023

2022
The Flores-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation.
Trans. Assoc. Comput. Linguistics, 2022

NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research.
CoRR, 2022

Multi-step Planning for Automated Hyperparameter Optimization with OptFormer.
CoRR, 2022

Towards Learning Universal Hyperparameter Optimizers with Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022


On Anytime Learning at Macroscale.
Proceedings of the Conference on Lifelong Learning Agents, 2022

2021
Residual Energy-Based Models for Text.
J. Mach. Learn. Res., 2021

Efficient Continual Learning with Modular Networks and Task-Driven Priors.
Proceedings of the 9th International Conference on Learning Representations, 2021

The Source-Target Domain Mismatch Problem in Machine Translation.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Discriminative Reranking for Neural Machine Translation.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Few-shot Sequence Learning with Transformers.
CoRR, 2020

Multi-scale Transformer Language Models.
CoRR, 2020

Energy-Based Models for Text.
CoRR, 2020

Revisiting Self-Training for Neural Sequence Generation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Residual Energy-Based Models for Text Generation.
Proceedings of the 8th International Conference on Learning Representations, 2020

On The Evaluation of Machine Translation SystemsTrained With Back-Translation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
On The Evaluation of Machine Translation Systems Trained With Back-Translation.
CoRR, 2019

Real or Fake? Learning to Discriminate Machine from Human Generated Text.
CoRR, 2019

Continual Learning with Tiny Episodic Memories.
CoRR, 2019

Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English.
CoRR, 2019

Large Memory Layers with Product Keys.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Mixture Models for Diverse Machine Translation: Tricks of the Trade.
Proceedings of the 36th International Conference on Machine Learning, 2019

Multiple-Attribute Text Rewriting.
Proceedings of the 7th International Conference on Learning Representations, 2019

Efficient Lifelong Learning with A-GEM.
Proceedings of the 7th International Conference on Learning Representations, 2019

Task-Driven Modular Networks for Zero-Shot Compositional Learning.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Facebook AI's WAT19 Myanmar-English Translation Task Submission.
Proceedings of the 6th Workshop on Asian Translation, 2019

2018
Multiple-Attribute Text Style Transfer.
CoRR, 2018

Lightweight Adaptive Mixture of Neural and N-gram Language Models.
CoRR, 2018

Classical Structured Prediction Losses for Sequence to Sequence Learning.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Analyzing Uncertainty in Neural Machine Translation.
Proceedings of the 35th International Conference on Machine Learning, 2018

Word translation without parallel data.
Proceedings of the 6th International Conference on Learning Representations, 2018

Unsupervised Machine Translation Using Monolingual Corpora Only.
Proceedings of the 6th International Conference on Learning Representations, 2018

Phrase-Based & Neural Unsupervised Machine Translation.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017
Unsupervised Machine Translation Using Monolingual Corpora Only.
CoRR, 2017

Training Language Models Using Target-Propagation.
CoRR, 2017

Gradient Episodic Memory for Continuum Learning.
CoRR, 2017

Transformation-Based Models of Video Sequences.
CoRR, 2017

Gradient Episodic Memory for Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Fader Networks: Manipulating Images by Sliding Attributes.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning through Dialogue Interactions by Asking Questions.
Proceedings of the 5th International Conference on Learning Representations, 2017

Dialogue Learning With Human-in-the-Loop.
Proceedings of the 5th International Conference on Learning Representations, 2017

Hard Mixtures of Experts for Large Scale Weakly Supervised Vision.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Sequence Level Training with Recurrent Neural Networks.
Proceedings of the 4th International Conference on Learning Representations, 2016

Learning Through Dialogue Interactions.
CoRR, 2016

2015
Guest Editorial: Deep Learning.
Int. J. Comput. Vis., 2015

Learning Longer Memory in Recurrent Neural Networks.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Scale-invariant learning and convolutional networks.
CoRR, 2015

Web-scale training for face identification.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Multi-GPU Training of ConvNets.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Video (language) modeling: a baseline for generative models of natural videos.
CoRR, 2014

On Learning Where To Look.
CoRR, 2014

Learning Factored Representations in a Deep Mixture of Experts.
Proceedings of the 2nd International Conference on Learning Representations, 2014

PANDA: Pose Aligned Networks for Deep Attribute Modeling.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

DeepFace: Closing the Gap to Human-Level Performance in Face Verification.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Modeling Natural Images Using Gated MRFs.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

DeViSE: A Deep Visual-Semantic Embedding Model.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Predicting Parameters in Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On rectified linear units for speech processing.
Proceedings of the IEEE International Conference on Acoustics, 2013

An empirical study of learning rates in deep neural networks for speech recognition.
Proceedings of the IEEE International Conference on Acoustics, 2013

Multilingual acoustic models using distributed deep neural networks.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Large Scale Distributed Deep Networks.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Building high-level features using large scale unsupervised learning.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
On Autoencoders and Score Matching for Energy Based Models.
Proceedings of the 28th International Conference on Machine Learning, 2011

On deep generative models with applications to recognition.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition
CoRR, 2010

Generating more realistic images using gated MRF's.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Modeling pixel means and covariances using factorized third-order boltzmann machines.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Unsupervised Learning of Feature Hierarchies.
PhD thesis, 2009

Unsupervised image ranking.
Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining, 2009

What is the best multi-stage architecture for object recognition?
Proceedings of the IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27, 2009

Learning invariant features through topographic filter maps.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008
Semi-supervised learning of compact document representations with deep networks.
Proceedings of the Machine Learning, 2008

2007
Automatic recognition of biological particles in microscopic images.
Pattern Recognit. Lett., 2007

A Unified Energy-Based Framework for Unsupervised Learning.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Sparse Feature Learning for Deep Belief Networks.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images.
Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

Energy-Based Models in Document Recognition and Computer Vision.
Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 2007

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006
Efficient Learning of Sparse Representations with an Energy-Based Model.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006


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