Y-Lan Boureau, Ph.D.
Affiliations: | 2012 | Computer Science | New York University, New York, NY, United States |
Area:
machine learning, computational neuroscience, computer visionGoogle:
"Y-Lan Boureau"Mean distance: 16.81 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentorYann LeCun | grad student | 2012 | NYU | |
(Learning Hierarchical Feature Extractors For Image Recognition.) | ||||
Jean Ponce | grad student | 2012 | NYU | |
(Learning Hierarchical Feature Extractors For Image Recognition.) |
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Publications
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Hori C, Perez J, Higashinaka R, et al. (2019) Overview of the sixth dialog system technology challenge: DSTC6 Computer Speech & Language. 55: 1-25 |
Boureau YL, Le Roux N, Bach F, et al. (2011) Ask the locals: Multi-way local pooling for image recognition Proceedings of the Ieee International Conference On Computer Vision. 2651-2658 |
Boureau YL, Bach F, LeCun Y, et al. (2010) Learning mid-level features for recognition Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2559-2566 |
Kavukcuoglu K, Sermanet P, Boureau YL, et al. (2010) Learning convolutional feature hierarchies for visual recognition Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 |
Boureau YL, Ponce J, Lecun Y. (2010) A theoretical analysis of feature pooling in visual recognition Icml 2010 - Proceedings, 27th International Conference On Machine Learning. 111-118 |
Ranzato M, Boureau YL, Le Cun Y. (2009) Sparse feature learning for deep belief networks Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference |
Ranzato M, Huang FJ, Boureau YL, et al. (2007) Unsupervised learning of invariant feature hierarchies with applications to object recognition Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition |
Ranzato M, Boureau YL, LeCun Y, et al. (2007) A unified energy-based framework for unsupervised learning Journal of Machine Learning Research. 2: 371-379 |