Intriguing properties of neural networks

2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings

Volumn , Issue , 2014, Pages

  Szegedy, Christian ^a   Zaremba, Wojciech ^b   Sutskever, Ilya ^a   Bruna, Joan ^b   Erhan, Dumitru ^a   Goodfellow, Ian ^c   Fergus, Rob ^b  

^a GOOGLE INC   (United States)

^b NEW YORK UNIVERSITY   (United States)

^c UNIVERSITÉ DE MONTRÉAL   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DEEP NEURAL NETWORKS; NETWORK LAYERS; SEMANTICS; SPEECH RECOGNITION;

INPUT-OUTPUT MAPPING; LINEAR COMBINATIONS; PREDICTION ERRORS; SEMANTIC INFORMATION; SPECIFIC NATURE; STATE-OF-THE-ART PERFORMANCE; VISUAL RECOGNITION;

MULTILAYER NEURAL NETWORKS;

EID: 85083953343     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, and Klaus-Robert Müller. How to explain individual classification decisions. The Journal of Machine Learning Research, 99:1803–1831, 2010.
2. Yoshua Bengio. Learning deep architectures for ai. Foundations and trends® in Machine Learning, 2(1):1–127, 2009.
3. Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. Imagenet: A large-scale hierarchical image database. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages 248–255. IEEE, 2009.
4. Dumitru Erhan, Yoshua Bengio, Aaron Courville, and Pascal Vincent. Visualizing higher-layer features of a deep network. Technical Report 1341, University of Montreal, June 2009. Also presented at the ICML 2009 Workshop on Learning Feature Hierarchies, Montréal, Canada.
5. Pedro Felzenszwalb, David McAllester, and Deva Ramanan. A discriminatively trained, multiscale, deformable part model. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pages 1–8. IEEE, 2008.
6. Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. arXiv preprint arXiv:1311.2524, 2013.
7. Ian Goodfellow, Quoc Le, Andrew Saxe, Honglak Lee, and Andrew Y Ng. Measuring invariances in deep networks. Advances in neural information processing systems, 22:646–654, 2009.
8. Geoffrey E. Hinton, Li Deng, Dong Yu, George E. Dahl, Abdel rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N. Sainath, and Brian Kingsbury. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Process. Mag., 29(6):82–97, 2012.
9. Alex Krizhevsky, Ilya Sutskever, and Geoff Hinton. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems 25, pages 1106–1114, 2012.
10. Quoc V Le, Marc’Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg S Corrado, Jeff Dean, and Andrew Y Ng. Building high-level features using large scale unsupervised learning. arXiv preprint arXiv:1112.6209, 2011.
11. Yann LeCun and Corinna Cortes. The mnist database of handwritten digits, 1998.
12. Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781, 2013.
13. Matthew D Zeiler and Rob Fergus. Visualizing and understanding convolutional neural networks. arXiv preprint arXiv:1311.2901, 2013.