Marc'Aurelio Ranzato, PhD - Publications

Affiliations: 
Google, Inc., Mountain View, CA, United States 
Area:
vision, learning, computational neuroscience
Website:
http://www.cs.toronto.edu/~ranzato/

24 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2015 Ranzato M’, Hinton G, LeCun Y. Guest Editorial: Deep Learning International Journal of Computer Vision. 113: 1-2. DOI: 10.1007/s11263-015-0813-1  0.48
2014 Taigman Y, Yang M, Ranzato M, Wolf L. DeepFace: Closing the gap to human-level performance in face verification Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1701-1708. DOI: 10.1109/CVPR.2014.220  1
2014 Zhang N, Paluri M, Ranzato M, Darrell T, Bourdev L. PANDA: Pose aligned networks for deep attribute modeling Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1637-1644. DOI: 10.1109/CVPR.2014.212  1
2013 Ranzato M, Mnih V, Susskind JM, Hinton GE. Modeling natural images using gated MRFs. Ieee Transactions On Pattern Analysis and Machine Intelligence. 35: 2206-22. PMID 23868780 DOI: 10.1109/TPAMI.2013.29  1
2013 Ranzato M, Mnih V, Susskind JM, Hinton GE. Modeling Natural Images Using Gated MRFs. Ieee Transactions On Pattern Analysis and Machine Intelligence. PMID 23358281  1
2013 Zeiler MD, Ranzato M, Monga R, Mao M, Yang K, Le QV, Nguyen P, Senior A, Vanhoucke V, Dean J, Hinton GE. On rectified linear units for speech processing Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 3517-3521. DOI: 10.1109/ICASSP.2013.6638312  1
2013 Denil M, Shakibi B, Dinh L, Ranzato M, De Freitas N. Predicting parameters in deep learning Advances in Neural Information Processing Systems 1
2011 Ranzato M, Susskind J, Mnih V, Hinton G. On deep generative models with applications to recognition Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2857-2864. DOI: 10.1109/CVPR.2011.5995710  1
2011 Swersky K, Ranzato M, Buchman D, Marlin BM, De Freitas N. On autoencoders and score matching for energy based models Proceedings of the 28th International Conference On Machine Learning, Icml 2011. 1201-1208.  1
2010 Ranzato M, Hinton GE. Modeling pixel means and covariances using factorized third-order Boltzmann machines Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2551-2558. DOI: 10.1109/CVPR.2010.5539962  1
2010 Ranzato MA, Mnih V, Hinton GE. Generating more realistic images using gated MRF's Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 1
2010 Ranzato M, Krizhevsky A, Hinton GE. Factored 3-way restricted Boltzmann machines for modeling natural images Journal of Machine Learning Research. 9: 621-628.  1
2010 Dahl GE, Ranzato M, Mohamed AR, Hinton G. Phone recognition with the mean-covariance restricted Boltzmann machine Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 1
2009 Hörster E, Slaney M, Ranzato M, Weinberger K. Unsupervised image ranking 1st Acm Workshop On Large-Scale Multimedia Retrieval and Mining, Ls-Mmrm 2009, Co-Located With the 2009 Acm International Conference On Multimedia, Mm'09. 81-88. DOI: 10.1145/1631058.1631074  1
2009 Jarrett K, Kavukcuoglu K, Ranzato M, LeCun Y. What is the best multi-stage architecture for object recognition? Proceedings of the Ieee International Conference On Computer Vision. 2146-2153. DOI: 10.1109/ICCV.2009.5459469  1
2009 Kavukcuoglu K, Ranzato M, Fergus R, LeCun Y. Learning invariant features through topographic filter maps 2009 Ieee Computer Society Conference On Computer Vision and Pattern Recognition Workshops, Cvpr Workshops 2009. 1605-1612. DOI: 10.1109/CVPRW.2009.5206545  1
2009 Ranzato M, Boureau YL, Le Cun Y. Sparse feature learning for deep belief networks Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 1
2008 Ranzato M, Szummer M. Semi-supervised learning of compact document representations with deep networks Proceedings of the 25th International Conference On Machine Learning. 792-799.  1
2007 LeCun Y, Chopra S, Ranzato MA, Huang FJ. Energy-based models in document recognition and computer vision Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 1: 337-341. DOI: 10.1109/ICDAR.2007.4378728  1
2007 Ranzato MA, LeCun Y. A sparse and locally shift invariant feature extractor applied to document images Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2: 1213-1217. DOI: 10.1109/ICDAR.2007.4377108  1
2007 Ranzato M, Huang FJ, Boureau YL, LeCun Y. Unsupervised learning of invariant feature hierarchies with applications to object recognition Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. DOI: 10.1109/CVPR.2007.383157  1
2007 Ranzato M, Taylor PE, House JM, Flagan RC, LeCun Y, Perona P. Automatic recognition of biological particles in microscopic images Pattern Recognition Letters. 28: 31-39. DOI: 10.1016/j.patrec.2006.06.010  1
2007 Ranzato M, Boureau YL, LeCun Y, Chopra S. A unified energy-based framework for unsupervised learning Journal of Machine Learning Research. 2: 371-379.  1
2007 Ranzato MA, Poultney C, Chopra S, LeCun Y. Efficient learning of sparse representations with an energy-based model Advances in Neural Information Processing Systems. 1137-1144.  1
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