Predicting parameters in deep learning
The recent success of large and deep neural network models has motivated the training of even larger and deeper networks with millions of parameters. Training these models usually requires parallel training methods where communicating large number of parameters becomes one of the main bottlenecks. W...
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| Language: | English |
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University of British Columbia
2014
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| Online Access: | http://hdl.handle.net/2429/50999 |