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If I understand the paper correctly, the architecture is very odd. As far as I can tell, it's equivalent to a deep CNN, with the facts being fed into every cou
by fpgaminer 11y ago
If I understand the paper correctly, the architecture is very odd. As far as I can tell, it's equivalent to a deep CNN, with the facts being fed into every couple layers. Why did they break it up into parallel invocations of DNNs, and several layers of DNNs? Very strange.
I imagine a simplified architecture of RNN->Highway CNN->Answerer would achieve better results while being more homogeneous.
- jbaiter 11y agoCan you explain what you mean with "Highway CNN"? It's the first time I've heard the term and Google doesn't help much either.
- 336f5 11y agohttp://arxiv.org/abs/1505.00387 http://arxiv.org/abs/1505.00387 Very deep NNs, which try to bypass the training difficulties in propagating error all the way from the bottom to the top by adding some special shortcuts between nodes in distant layers.