933 citations · 6k across the 51 of their papers we have counts for
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Multi-GPU Training of ConvNets
Omry Yadan, Keith Adams, Yaniv Taigman +1
In this work we evaluate different approaches to parallelize computation of convolutional neural networks across several GPUs.
Learning Factored Representations in a Deep Mixture of Experts
David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever
Mixtures of Experts combine the outputs of several "expert" networks, each of which specializes in a different part of the input space. This is achieved by training a "gating" netw…
PANDA: Pose Aligned Networks for Deep Attribute Modeling
Ning Zhang, Manohar Paluri, Marc'Aurelio Ranzato +2
We propose a method for inferring human attributes (such as gender, hair style, clothes style, expression, action) from images of people under large variation of viewpoint, pose, a…
Predicting Parameters in Deep Learning
Misha Denil, Babak Shakibi, Laurent Dinh +2
We demonstrate that there is significant redundancy in the parameterization of several deep learning models. Given only a few weight values for each feature it is possible to accur…