[biomodel]

Not sure why anyone would use 2D CNNs for processing text when there is no spatial correlation in the embedding features. Recent work such as https://arxiv.org/abs/1803.01271 show that for most tasks, 1D CNNs outperform recurrent architectures while being faster to train

[madavidj]

Probably because the author followed this blog: http://www.wildml.com/2015/12/implementing-a-cnn-for-text-cl...

That blog used a 2d cnn because tensorflow didn't have a 1d version at the time of writing, so he just created a dummy 2nd dimension of length 1 and called it a day.

[soraki_soladead]

This is just a bug in their code. The paper they cite uses 1D convolutions. Though, I suppose having an unused dimension only really hurts efficiency.

[gnulinux]

> Though, I suppose having an unused dimension only really hurts efficiency.

That might not be true as it might increase bias and thus might need a more careful hyperparameter tuning to avoid overfitting.