PUBLICATIONS

[23] M.D. Zeiler, M. Ranzato, R. Monga, M. Mao, K. Yang, Q.V. Le, P. Nguyen, A. Senior, V. Vanhoucke, J. Dean, G. Hinton " On Rectified Linear Units for Speech Processing". IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP 2013) Vancouver, 2013.

[22] G. Heigold, V. Vanhoucke, A. Senior, P. Nguyen, M. Ranzato, M. Devin, J. Dean "Multilingual Acoustic Models using Distributed Neep Neural Networks". IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP 2013) Vancouver, 2013.

[21] A. Senior, G. Heigold, M. Ranzato, K. Yang "An Empirical Study of Learning Rates in Deep Neural Networks for Speech Recognition". IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP 2013) Vancouver, 2013.

[20] M. Ranzato, V. Mnih, J, Susskind, G. Hinton, "Modeling Natural Images Using Gated MRFs ". IEEE Trans. Pattern Analysis and Machine Intelligence, ??-? vol.??, 2013

[19] J. Dean, G. Corrado, R. Monga, K. Chen, M. Devin, Q. Le, M. Mao, M. Ranzato, A. Senior, P. Tucker, K. Yang, A. Ng " Large Scale Distributed Deep Networks". Advances in Neural Information Processing Systems 25 (NIPS 2012), Lake Tahoe, 2012.

[18] Q. Le, M. Ranzato, R. Monga, M. Devin, G. Corrado, K. Chen, J. Dean, A. Ng. "Building High-Level Features Using Large Scale Unsupervised Learning". International Conference of Machine Learning (ICML 2012), Edinburgh, 2012. [supplementary material]

[17] K. Swersky, M. Ranzato, D. Buchman, B.M. Marlin, N. de Freitas. "On Autoencoders and Score Matching for Energy Based Models". International Conference of Machine Learning (ICML 2011), Bellevue, 2011.

[16] M. Ranzato, J, Susskind, V. Mnih, G. Hinton, "On Deep Generative Models with Applications to Recognition ". Proc. of Computer Vision and Pattern Recognition Conference (CVPR 2011), Colarodo Springs, 2011.

[15] M. Ranzato, V. Mnih, G. Hinton, "Generating More Realistic Images Using Gated MRF's". Advances in Neural Information Processing Systems 23 (NIPS 2010), Vancouver, 2010. [code]

[14] G. Dahl, M. Ranzato, A. Mohamed, G. Hinton, "Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine ".Advances in Neural Information Processing Systems 23 (NIPS 2010), Vancouver, 2010.

[13] M. Ranzato, G. Hinton, "Modeling Pixel Means and Covariances Using Factorized Third-Order Boltzmann Machines". Proc. of Computer Vision and Pattern Recognition Conference (CVPR 2010), San Francisco, 2010. [code]

[12] M. Ranzato, A. Krizhevsky, G. Hinton, "Factored 3-Way Restricted Boltzmann Machines for Modeling Natural Images". Proc. of the 13-th International Conference on Artificial Intelligence and Statistics (AISTATS 2010), Italy, 2010. [code]

[11] K. Jarrett, K. Kavukcuoglu, M. Ranzato, Y. LeCun. "What is the Best Multi-Stage Architecture for Object Recognition?". Proc. of International Conference on Computer Vision (ICCV 2009), 2009. [code]

[10] K. Kavukcuoglu, M. Ranzato, R. Fergus, Y. LeCun. "Learning Invariant Features through Topographic Filter Maps". Proc. of Computer Vision and Pattern Recognition Conference (CVPR 2009), Miami, 2009. [code]

[9] M. Ranzato, M. Szummer. "Semi-supervised Learning of Compact Document Representations with Deep Networks". International Conference of Machine Learning (ICML 2008), Helsinki, 2008.

[8] M. Ranzato, Y. Boureau, Y. LeCun. "Sparse Feature Learning for Deep Belief Networks". Advances in Neural Information Processing Systems 20 (NIPS 2007).

[7] M. Ranzato, Y. LeCun, "A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images". International Conference on Document Analysis and Recognition (ICDAR 2007), Curitiba, 2007.

[6] Y. LeCun, S. Chopra, M. Ranzato, F.J. Huang "Energy-Based Models in Document Recognition and Computer Vision". International Conference on Document Analysis and Recognition (ICDAR 2007), Curitiba, 2007.

[5] M. Ranzato, F.J. Huang, Y. Boureau, Y. LeCun, "Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition". Proc. of Computer Vision and Pattern Recognition Conference (CVPR 2007), Minneapolis, 2007.

[4] M. Ranzato, Y. Boureau, S. Chopra, Y. LeCun, "A Unified Energy-Based Framework for Unsupervised Learning" Proc. of the 11-th International Workshop on Artificial Intelligence and Statistics (AISTATS 2007), Puerto Rico, 2007.

[3] M. Ranzato, P.E. Taylor, J.M. House, R.C. Flagan, Y. LeCun and P. Perona. "Automatic Recognition of Biological Particles in Microscopic Images". Pattern Recognition Letters, Volume 28, Issue 1, 1 January 2007, pp.31-39.

[2] M. Ranzato, C.S. Poultney, S. Chopra and Y. LeCun. "Efficient Learning of Sparse Overcomplete Representations with an Energy-Based Model". Advances in Neural Information Processing Systems 19 (NIPS 2006).

[1] Y. LeCun, S. Chopra, R. Hadsell, M. Ranzato and F.J. Huang. "A Tutorial on Energy-Based Learning" in Bakir et al. (eds) "Predicting Structured Outputs", MIT Press 2006.

Ph.D. Thesis

"Unsupervised Learning of Feature Hierarchies". New York University, May 2009.

Technical Reports

K. Kavukcuoglu, M. Ranzato, Y. LeCun. "Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition". CBLL Technical Report, December 2008. ArXiv 1010.3467. [code]

Workshop Papers

E. Hörster, M. Slaney, M. Ranzato, K. Weinberger "Unsupervised Image Ranking". Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining, Beijing, 2009.

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