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ORCIDMarc'Aurelio Ranzato
Person information
- affiliation: DeepMind, London, UK
- affiliation: Facebook AI Research, New York City, NY, USA
- affiliation: Google, Maintain View, CA, USA
- affiliation (PhD 2009): New York University, New York City, NY, USA
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2020 – today
- 2024
[i48]Bo Liu, Rachita Chhaparia, Arthur Douillard, Satyen Kale, Andrei A. Rusu, Jiajun Shen, Arthur Szlam, Marc'Aurelio Ranzato:
Asynchronous Local-SGD Training for Language Modeling. CoRR abs/2401.09135 (2024)- [i47]Arthur Douillard, Qixuan Feng, Andrei A. Rusu, Adhiguna Kuncoro, Yani Donchev, Rachita Chhaparia, Ionel Gog, Marc'Aurelio Ranzato, Jiajun Shen, Arthur Szlam:
DiPaCo: Distributed Path Composition. CoRR abs/2403.10616 (2024) - 2023
- [j6]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. J. Mach. Learn. Res. 24: 308:1-308:77 (2023) - [i46]Massimo Caccia, Alexandre Galashov, Arthur Douillard, Amal Rannen-Triki, Dushyant Rao, Michela Paganini, Laurent Charlin, Marc'Aurelio Ranzato, Razvan Pascanu:
Towards Compute-Optimal Transfer Learning. CoRR abs/2304.13164 (2023) - [i45]Adam Fisch, Amal Rannen-Triki, Razvan Pascanu, Jörg Bornschein, Angeliki Lazaridou, Elena Gribovskaya, Marc'Aurelio Ranzato:
Towards Robust and Efficient Continual Language Learning. CoRR abs/2307.05741 (2023) - [i44]Arthur Douillard, Qixuang Feng, Andrei A. Rusu, Rachita Chhaparia, Yani Donchev, Adhiguna Kuncoro, Marc'Aurelio Ranzato, Arthur Szlam, Jiajun Shen:
DiLoCo: Distributed Low-Communication Training of Language Models. CoRR abs/2311.08105 (2023) - 2022
- [j5]Naman Goyal, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc'Aurelio Ranzato, Francisco Guzmán, Angela Fan:
The Flores-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation. Trans. Assoc. Comput. Linguistics 10: 522-538 (2022) - [c57]Lucas Caccia, Jing Xu, Myle Ott, Marc'Aurelio Ranzato, Ludovic Denoyer:
On Anytime Learning at Macroscale. CoLLAs 2022: 165-182 - [c56]Aidan Clark, Diego de Las Casas, Aurelia Guy, Arthur Mensch, Michela Paganini, Jordan Hoffmann, Bogdan Damoc, Blake A. Hechtman, Trevor Cai, Sebastian Borgeaud, George van den Driessche, Eliza Rutherford, Tom Hennigan, Matthew J. Johnson, Albin Cassirer, Chris Jones, Elena Buchatskaya, David Budden, Laurent Sifre, Simon Osindero, Oriol Vinyals, Marc'Aurelio Ranzato, Jack W. Rae, Erich Elsen, Koray Kavukcuoglu, Karen Simonyan:
Unified Scaling Laws for Routed Language Models. ICML 2022: 4057-4086 - [c55]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 2022 - [i43]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR abs/2205.13320 (2022) - [i42]Lucio M. Dery, Abram L. Friesen, Nando de Freitas, Marc'Aurelio Ranzato, Yutian Chen:
Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. CoRR abs/2210.04971 (2022) - [i41]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuang Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. CoRR abs/2211.11747 (2022) - 2021
- [j4]Anton Bakhtin, Yuntian Deng, Sam Gross, Myle Ott, Marc'Aurelio Ranzato, Arthur Szlam:
Residual Energy-Based Models for Text. J. Mach. Learn. Res. 22: 40:1-40:41 (2021) - [c54]Ann Lee, Michael Auli, Marc'Aurelio Ranzato:
Discriminative Reranking for Neural Machine Translation. ACL/IJCNLP (1) 2021: 7250-7264 - [c53]Jiajun Shen
, Peng-Jen Chen, Matt Le, Junxian He, Jiatao Gu, Myle Ott, Michael Auli, Marc'Aurelio Ranzato:
The Source-Target Domain Mismatch Problem in Machine Translation. EACL 2021: 1519-1533 - [c52]Tom Veniat, Ludovic Denoyer, Marc'Aurelio Ranzato:
Efficient Continual Learning with Modular Networks and Task-Driven Priors. ICLR 2021 - [e2]Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. 2021 [contents] - [i40]Naman Goyal, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc'Aurelio Ranzato, Francisco Guzmán, Angela Fan:
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation. CoRR abs/2106.03193 (2021) - [i39]Lucas Caccia, Jing Xu, Myle Ott, Marc'Aurelio Ranzato, Ludovic Denoyer:
On Anytime Learning at Macroscale. CoRR abs/2106.09563 (2021) - 2020
- [c51]Sergey Edunov, Myle Ott, Marc'Aurelio Ranzato, Michael Auli:
On The Evaluation of Machine Translation SystemsTrained With Back-Translation. ACL 2020: 2836-2846 - [c50]Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, Marc'Aurelio Ranzato:
Residual Energy-Based Models for Text Generation. ICLR 2020 - [c49]Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato:
Revisiting Self-Training for Neural Sequence Generation. ICLR 2020 - [e1]Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin:
Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020 [contents] - [i38]Anton Bakhtin, Yuntian Deng, Sam Gross, Myle Ott, Marc'Aurelio Ranzato, Arthur Szlam:
Energy-Based Models for Text. CoRR abs/2004.10188 (2020) - [i37]Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, Marc'Aurelio Ranzato:
Residual Energy-Based Models for Text Generation. CoRR abs/2004.11714 (2020) - [i36]Sandeep Subramanian, Ronan Collobert, Marc'Aurelio Ranzato, Y-Lan Boureau:
Multi-scale Transformer Language Models. CoRR abs/2005.00581 (2020) - [i35]Lajanugen Logeswaran, Ann Lee, Myle Ott, Honglak Lee, Marc'Aurelio Ranzato, Arthur Szlam:
Few-shot Sequence Learning with Transformers. CoRR abs/2012.09543 (2020) - [i34]Tom Veniat, Ludovic Denoyer, Marc'Aurelio Ranzato:
Efficient Continual Learning with Modular Networks and Task-Driven Priors. CoRR abs/2012.12631 (2020)
2010 – 2019
- 2019
- [c48]Peng-Jen Chen, Jiajun Shen, Matt Le, Vishrav Chaudhary, Ahmed El-Kishky, Guillaume Wenzek, Myle Ott, Marc'Aurelio Ranzato:
Facebook AI's WAT19 Myanmar-English Translation Task Submission. WAT@EMNLP-IJCNLP 2019: 112-122 - [c47]Francisco Guzmán, Peng-Jen Chen, Myle Ott, Juan Miguel Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, Marc'Aurelio Ranzato:
The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English. EMNLP/IJCNLP (1) 2019: 6097-6110 - [c46]Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc'Aurelio Ranzato:
Task-Driven Modular Networks for Zero-Shot Compositional Learning. ICCV 2019: 3592-3601 - [c45]Arslan Chaudhry, Marc'Aurelio Ranzato, Marcus Rohrbach, Mohamed Elhoseiny:
Efficient Lifelong Learning with A-GEM. ICLR (Poster) 2019 - [c44]Guillaume Lample, Sandeep Subramanian, Eric Michael Smith, Ludovic Denoyer, Marc'Aurelio Ranzato, Y-Lan Boureau:
Multiple-Attribute Text Rewriting. ICLR (Poster) 2019 - [c43]Tianxiao Shen, Myle Ott, Michael Auli, Marc'Aurelio Ranzato:
Mixture Models for Diverse Machine Translation: Tricks of the Trade. ICML 2019: 5719-5728 - [c42]Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou:
Large Memory Layers with Product Keys. NeurIPS 2019: 8546-8557 - [i33]Francisco Guzmán, Peng-Jen Chen, Myle Ott, Juan Miguel Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, Marc'Aurelio Ranzato:
Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English. CoRR abs/1902.01382 (2019) - [i32]Tianxiao Shen, Myle Ott, Michael Auli, Marc'Aurelio Ranzato:
Mixture Models for Diverse Machine Translation: Tricks of the Trade. CoRR abs/1902.07816 (2019) - [i31]Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H. S. Torr, Marc'Aurelio Ranzato:
Continual Learning with Tiny Episodic Memories. CoRR abs/1902.10486 (2019) - [i30]Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc'Aurelio Ranzato:
Task-Driven Modular Networks for Zero-Shot Compositional Learning. CoRR abs/1905.05908 (2019) - [i29]Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc'Aurelio Ranzato, Arthur Szlam:
Real or Fake? Learning to Discriminate Machine from Human Generated Text. CoRR abs/1906.03351 (2019) - [i28]Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou:
Large Memory Layers with Product Keys. CoRR abs/1907.05242 (2019) - [i27]Sergey Edunov, Myle Ott, Marc'Aurelio Ranzato, Michael Auli:
On The Evaluation of Machine Translation Systems Trained With Back-Translation. CoRR abs/1908.05204 (2019) - [i26]Jiajun Shen, Peng-Jen Chen, Matt Le, Junxian He, Jiatao Gu, Myle Ott, Michael Auli, Marc'Aurelio Ranzato:
The Source-Target Domain Mismatch Problem in Machine Translation. CoRR abs/1909.13151 (2019) - [i25]Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato:
Revisiting Self-Training for Neural Sequence Generation. CoRR abs/1909.13788 (2019) - [i24]Peng-Jen Chen, Jiajun Shen, Matt Le, Vishrav Chaudhary, Ahmed El-Kishky, Guillaume Wenzek, Myle Ott, Marc'Aurelio Ranzato:
Facebook AI's WAT19 Myanmar-English Translation Task Submission. CoRR abs/1910.06848 (2019) - 2018
- [c41]Guillaume Lample, Myle Ott, Alexis Conneau, Ludovic Denoyer, Marc'Aurelio Ranzato:
Phrase-Based & Neural Unsupervised Machine Translation. EMNLP 2018: 5039-5049 - [c40]Guillaume Lample, Alexis Conneau, Ludovic Denoyer, Marc'Aurelio Ranzato:
Unsupervised Machine Translation Using Monolingual Corpora Only. ICLR (Poster) 2018 - [c39]Guillaume Lample, Alexis Conneau, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou:
Word translation without parallel data. ICLR (Poster) 2018 - [c38]Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Analyzing Uncertainty in Neural Machine Translation. ICML 2018: 3953-3962 - [c37]Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Classical Structured Prediction Losses for Sequence to Sequence Learning. NAACL-HLT 2018: 355-364 - [i23]Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Analyzing Uncertainty in Neural Machine Translation. CoRR abs/1803.00047 (2018) - [i22]Anton Bakhtin, Arthur Szlam, Marc'Aurelio Ranzato, Edouard Grave:
Lightweight Adaptive Mixture of Neural and N-gram Language Models. CoRR abs/1804.07705 (2018) - [i21]Guillaume Lample, Myle Ott, Alexis Conneau, Ludovic Denoyer, Marc'Aurelio Ranzato:
Phrase-Based & Neural Unsupervised Machine Translation. CoRR abs/1804.07755 (2018) - [i20]Sandeep Subramanian, Guillaume Lample, Eric Michael Smith, Ludovic Denoyer, Marc'Aurelio Ranzato, Y-Lan Boureau:
Multiple-Attribute Text Style Transfer. CoRR abs/1811.00552 (2018) - [i19]Arslan Chaudhry, Marc'Aurelio Ranzato, Marcus Rohrbach, Mohamed Elhoseiny:
Efficient Lifelong Learning with A-GEM. CoRR abs/1812.00420 (2018) - 2017
- [c36]Sam Gross, Marc'Aurelio Ranzato, Arthur Szlam:
Hard Mixtures of Experts for Large Scale Weakly Supervised Vision. CVPR 2017: 5085-5093 - [c35]Jiwei Li, Alexander H. Miller, Sumit Chopra, Marc'Aurelio Ranzato, Jason Weston:
Dialogue Learning With Human-in-the-Loop. ICLR (Poster) 2017 - [c34]Jiwei Li, Alexander H. Miller, Sumit Chopra, Marc'Aurelio Ranzato, Jason Weston:
Learning through Dialogue Interactions by Asking Questions. ICLR (Poster) 2017 - [c33]Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, Marc'Aurelio Ranzato:
Fader Networks: Manipulating Images by Sliding Attributes. NIPS 2017: 5967-5976 - [c32]David Lopez-Paz, Marc'Aurelio Ranzato:
Gradient Episodic Memory for Continual Learning. NIPS 2017: 6467-6476 - [i18]Joost R. van Amersfoort, Anitha Kannan, Marc'Aurelio Ranzato, Arthur Szlam, Du Tran, Soumith Chintala:
Transformation-Based Models of Video Sequences. CoRR abs/1701.08435 (2017) - [i17]Sam Wiseman, Sumit Chopra, Marc'Aurelio Ranzato, Arthur Szlam, Ruoyu Sun, Soumith Chintala, Nicolas Vasilache:
Training Language Models Using Target-Propagation. CoRR abs/1702.04770 (2017) - [i16]Sam Gross, Marc'Aurelio Ranzato, Arthur Szlam:
Hard Mixtures of Experts for Large Scale Weakly Supervised Vision. CoRR abs/1704.06363 (2017) - [i15]Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, Marc'Aurelio Ranzato:
Fader Networks: Manipulating Images by Sliding Attributes. CoRR abs/1706.00409 (2017) - [i14]David Lopez-Paz, Marc'Aurelio Ranzato:
Gradient Episodic Memory for Continuum Learning. CoRR abs/1706.08840 (2017) - [i13]Alexis Conneau, Guillaume Lample, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou:
Word Translation Without Parallel Data. CoRR abs/1710.04087 (2017) - [i12]Guillaume Lample, Ludovic Denoyer, Marc'Aurelio Ranzato:
Unsupervised Machine Translation Using Monolingual Corpora Only. CoRR abs/1711.00043 (2017) - [i11]Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato:
Classical Structured Prediction Losses for Sequence to Sequence Learning. CoRR abs/1711.04956 (2017) - 2016
- [c31]Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli, Wojciech Zaremba:
Sequence Level Training with Recurrent Neural Networks. ICLR (Poster) 2016 - [i10]Jiwei Li, Alexander H. Miller, Sumit Chopra, Marc'Aurelio Ranzato, Jason Weston:
Dialogue Learning With Human-In-The-Loop. CoRR abs/1611.09823 (2016) - [i9]Jiwei Li, Alexander H. Miller, Sumit Chopra, Marc'Aurelio Ranzato, Jason Weston:
Learning Through Dialogue Interactions. CoRR abs/1612.04936 (2016) - 2015
- [j3]Marc'Aurelio Ranzato, Geoffrey E. Hinton, Yann LeCun:
Guest Editorial: Deep Learning. Int. J. Comput. Vis. 113(1): 1-2 (2015) - [c30]Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf:
Web-scale training for face identification. CVPR 2015: 2746-2754 - [c29]Grégoire Mesnil, Tomás Mikolov, Marc'Aurelio Ranzato, Yoshua Bengio:
Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews. ICLR (Workshop) 2015 - [c28]Tomás Mikolov, Armand Joulin, Sumit Chopra, Michaël Mathieu, Marc'Aurelio Ranzato:
Learning Longer Memory in Recurrent Neural Networks. ICLR (Workshop) 2015 - [i8]Soumith Chintala, Marc'Aurelio Ranzato, Arthur Szlam, Yuandong Tian, Mark Tygert, Wojciech Zaremba:
Scale-invariant learning and convolutional networks. CoRR abs/1506.08230 (2015) - 2014
- [c27]Ning Zhang, Manohar Paluri, Marc'Aurelio Ranzato, Trevor Darrell, Lubomir D. Bourdev:
PANDA: Pose Aligned Networks for Deep Attribute Modeling. CVPR 2014: 1637-1644 - [c26]Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf:
DeepFace: Closing the Gap to Human-Level Performance in Face Verification. CVPR 2014: 1701-1708 - [c25]David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever:
Learning Factored Representations in a Deep Mixture of Experts. ICLR (Workshop Poster) 2014 - [c24]Omry Yadan, Keith Adams, Yaniv Taigman, Marc'Aurelio Ranzato:
Multi-GPU Training of ConvNets. ICLR (Workshop Poster) 2014 - [i7]Marc'Aurelio Ranzato:
On Learning Where To Look. CoRR abs/1405.5488 (2014) - [i6]Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf:
Web-Scale Training for Face Identification. CoRR abs/1406.5266 (2014) - [i5]Marc'Aurelio Ranzato, Arthur Szlam, Joan Bruna, Michaël Mathieu, Ronan Collobert, Sumit Chopra:
Video (language) modeling: a baseline for generative models of natural videos. CoRR abs/1412.6604 (2014) - 2013
- [j2]Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton:
Modeling Natural Images Using Gated MRFs. IEEE Trans. Pattern Anal. Mach. Intell. 35(9): 2206-2222 (2013) - [c23]Matthew D. Zeiler, Marc'Aurelio Ranzato, Rajat Monga, Mark Z. Mao, K. Yang, Quoc Viet Le, Patrick Nguyen, Andrew W. Senior, Vincent Vanhoucke, Jeffrey Dean, Geoffrey E. Hinton:
On rectified linear units for speech processing. ICASSP 2013: 3517-3521 - [c22]Andrew W. Senior, Georg Heigold, Marc'Aurelio Ranzato, Ke Yang:
An empirical study of learning rates in deep neural networks for speech recognition. ICASSP 2013: 6724-6728 - [c21]Georg Heigold, Vincent Vanhoucke, Andrew W. Senior, Patrick Nguyen, Marc'Aurelio Ranzato, Matthieu Devin, Jeffrey Dean:
Multilingual acoustic models using distributed deep neural networks. ICASSP 2013: 8619-8623 - [c20]Andrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomás Mikolov:
DeViSE: A Deep Visual-Semantic Embedding Model. NIPS 2013: 2121-2129 - [c19]Misha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas:
Predicting Parameters in Deep Learning. NIPS 2013: 2148-2156 - [i4]Misha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas:
Predicting Parameters in Deep Learning. CoRR abs/1306.0543 (2013) - [i3]Ning Zhang, Manohar Paluri, Marc'Aurelio Ranzato, Trevor Darrell, Lubomir D. Bourdev:
PANDA: Pose Aligned Networks for Deep Attribute Modeling. CoRR abs/1311.5591 (2013) - 2012
- [c18]Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng:
Building high-level features using large scale unsupervised learning. ICML 2012 - [c17]Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng:
Large Scale Distributed Deep Networks. NIPS 2012: 1232-1240 - 2011
- [c16]Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton:
On deep generative models with applications to recognition. CVPR 2011: 2857-2864 - [c15]Kevin Swersky, Marc'Aurelio Ranzato, David Buchman, Benjamin M. Marlin, Nando de Freitas:
On Autoencoders and Score Matching for Energy Based Models. ICML 2011: 1201-1208 - [i2]Quoc V. Le, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Marc'Aurelio Ranzato, Jeffrey Dean, Andrew Y. Ng:
Building high-level features using large scale unsupervised learning. CoRR abs/1112.6209 (2011) - 2010
- [c14]Marc'Aurelio Ranzato, Geoffrey E. Hinton:
Modeling pixel means and covariances using factorized third-order boltzmann machines. CVPR 2010: 2551-2558 - [c13]George E. Dahl, Marc'Aurelio Ranzato, Abdel-rahman Mohamed, Geoffrey E. Hinton:
Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine. NIPS 2010: 469-477 - [c12]Marc'Aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton:
Generating more realistic images using gated MRF's. NIPS 2010: 2002-2010 - [c11]Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E. Hinton:
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images. AISTATS 2010: 621-628 - [i1]Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCun:
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition. CoRR abs/1010.3467 (2010)
2000 – 2009
- 2009
- [b1]Marc'Aurelio Ranzato:
Unsupervised Learning of Feature Hierarchies. New York University, USA, 2009 - [c10]Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergus, Yann LeCun:
Learning invariant features through topographic filter maps. CVPR 2009: 1605-1612 - [c9]Kevin Jarrett, Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCun:
What is the best multi-stage architecture for object recognition? ICCV 2009: 2146-2153 - [c8]Eva Hörster, Malcolm Slaney, Marc'Aurelio Ranzato, Kilian Q. Weinberger:
Unsupervised image ranking. LS-MMRM@ACM Multimedia 2009: 81-88 - 2008
- [c7]Marc'Aurelio Ranzato, Martin Szummer:
Semi-supervised learning of compact document representations with deep networks. ICML 2008: 792-799 - 2007
- [j1]Marc'Aurelio Ranzato, P. E. Taylor, James M. House, R. C. Flagan, Yann LeCun, Pietro Perona:
Automatic recognition of biological particles in microscopic images. Pattern Recognit. Lett. 28(1): 31-39 (2007) - [c6]Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau, Yann LeCun:
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition. CVPR 2007 - [c5]Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu Jie Huang:
Energy-Based Models in Document Recognition and Computer Vision. ICDAR 2007: 337-341 - [c4]Marc'Aurelio Ranzato, Yann LeCun:
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images. ICDAR 2007: 1213-1217 - [c3]Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun:
Sparse Feature Learning for Deep Belief Networks. NIPS 2007: 1185-1192 - [c2]Marc'Aurelio Ranzato, Y-Lan Boureau, Sumit Chopra, Yann LeCun:
A Unified Energy-Based Framework for Unsupervised Learning. AISTATS 2007: 371-379 - 2006
- [c1]Marc'Aurelio Ranzato, Christopher S. Poultney, Sumit Chopra, Yann LeCun:
Efficient Learning of Sparse Representations with an Energy-Based Model. NIPS 2006: 1137-1144
Coauthor Index
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