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Neural Networks with Few Multiplications
Published on May 27, 20162328 Views
For most deep learning algorithms training is notoriously time consuming. Since most of the computation in training neural networks is typically spent on floating point multiplications, we investigate
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Chapter list
Neural Networks with Few Multiplications00:00
Why we don’t want massive multiplications?00:36
Various trials in the past decades …01:37
Binarization as regularization?02:07
Our approach - 103:00
Our approach - 203:14
Binarize Weight Values - 103:19
Untitled03:19
Binarize Weight Values - 204:34
Our Approach - 304:55
Quantized Backprop - 105:07
Exponential Quantization05:48
Quantized Backprop - 206:28
Quantized Backprop - 306:56
How many multiplications saved?07:25
Range of Hidden Representations08:11
The Effect of Limiting the Range of Exponent08:50
General Performance09:13
Related Works & Recent Advances09:41
Any questions?10:24