Download Random Synaptic Feedback Weights Support Error Backpropagation For Deep Learning PDF Free - Full Version
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About Random Synaptic Feedback Weights Support Error Backpropagation For Deep Learning
Random synaptic feedback weights can effectively propagate error signals in neural networks and support error backpropagation learning. The study presents a new deep learning algorithm called "feedback alignment" that replaces the precise, symmetric feedback weights required by backpropagation with random feedback weights. Surprisingly, feedback alignment is as effective as backpropagation on a variety of tasks, avoids the need to transport synaptic weight information, and achieves backpropagation-like learning performance despite only modest symmetry between forward and backward connections. The findings help reopen questions about how the brain could implement error-driven learning and dispel assumptions that precise, symmetric connectivity is required.
Detailed Information
| Author: | ['Sherjil Ozair'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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