Gary Anthes
Abstract
Advances on multiple fronts are bringing big improvements to the way computers learn, increasing the accuracy of speech and vision systems.
- Le, Q. and seven others Building High-level Features Using Large Scale Unsupervised Learning, Proceedings of the 29th International Conference on Machine Learning, Edinburgh, Scotland, 2012.Google Scholar
- Dahl, G., Yu, D., Deng, L., and Acero, A. Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition, draft accepted by IEEE Transactions on Audio, Speech, and Language Processing, http://research. microsoft.com/pubs/144412/dbn4lvcsrtransaslp. pdf Google ScholarDigital Library
- Hinton, G. Brains, Sex, and Machine Learning, GoogleTechTalks (video), June 22, 2012 http://www.youtube.com/ watch?feature=player_ embedded&v=DleXA5ADG78#!Google Scholar
- Krizhevsky, A., Sutskever, I., and Hinton, G. ImageNet Classification with Deep Convolutional Neural Networks, paper to appear in Proceedings of the Neural Information Processing Systems Foundation 2012 conference, Lake Tahoe, NV http://www.image-net.org/challenges/ LSVRC/2012/supervision.pdfGoogle Scholar
- LeCun, Y., Kavukvuoglu, K., and Farabet, C. Convolutional Networks and Applications in Vision, Proc. International Symposium on Circuits and Systems, IEEE, 2010 http:// yann.lecun.com/exdb/publis/pdf/lecuniscas10.pdfGoogle ScholarCross Ref
Index Terms
- Deep learning comes of age
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