Deep Learning papers at ICML 2010

From the list of accepted papers, judging by title only:

Learning Fast Approximations of Sparse Coding
Karol Gregor, Yann LeCun

Boosted Backpropagation Learning for Training Deep Modular Networks
Alexander Grubb, Drew Bagnell

Deep learning via Hessian-free optimization
James Martens

3D Convolutional Neural Networks for Human Action Recognition
Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu

Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Phil Long, Rocco Servedio

Deep Supervised T-Distributed Embedding
Renqiang Min, Zineng Yuan, Laurens van der Maaten, Anthony Bonner, Zhaolei Zhang

Deep networks for robust visual recognition
Yichuan Tang, Chris Eliasmith

Rectified Linear Units Improve Restricted Boltzmann Machines
Vinod Nair, Geoffrey Hinton

Learning Deep Boltzmann Machines using Adaptive MCMC
Ruslan Salakhutdinov

A theoretical analysis of feature pooling in vision algorithms
Y-Lan Boureau, Jean Ponce, Yann LeCun

Deep networks for robust visual recognition
Yichuan Tang, Chris Eliasmith

4 comments to Deep Learning papers at ICML 2010

  • George

    Not also judging by author list?

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