Visualizing + Devil in Details + Intriguing Properties

Recurrent Neural Networks + AISTATS 2010

• Recurrent-Neural Networks [X]
• Graves, Mohamed and Hinton. Speech recognition with Deep Recurrent Neural Networks. [http://arxiv.org/abs/1303.5778]
• Unsupervised + Supervised [JW]
• Erhan, Courville, Bengio, Vincent. Why does unsupervised pre-training help deep learning?. AISTATS 2010 [PDF]

Supervised Learning

Supervised Learning

• Convolutional Networks (MNIST) [I]
• Handwritten digit recognition with a back-propagation network, Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard and L. D. Jackel (NIPS 1989) [PDF]
  
• Alex NET (ImageNet Challenge) [I]
• A. Krizhevsky, I. Sutskever, and G. E. Hinton. ImageNet classification with deep convolutional neural networks. In NIPS 2012. [PDF]

• Visualizing Deep Networks [D]
• M. D. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. ECCV 2014 [http://arxiv.org/abs/1311.2901]

Discussions - Unsupervised Learning

Papers

Unsupervised Learning

• AutoEncoders [C]
• Olsahausen and Field. Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1? PDF
• Restricted Boltzmann Machines [C]
• Hinton, G. E., Osindero, S. and Teh, Y. (2006)
  A fast learning algorithm for deep belief nets. PDF
• R-CNN [X]
• Q. Le, M. Ranzato, R. Monga, M. Devin, K. Chen, G. Corrado, J. Dean, and A. Ng. Building high-level features using large scale unsupervised learning. In Proc. ICML, 2012. [PDF]