Journal of Big Data

Table 1 Neural network parameters for networks used to test character embeddings and padded vs. non-padded convolutonal layers

From: Improving deep neural network design with new text data representations

1-ofm vs. log(m) embedding
	log-m			1-of-m
Convolutional layer	Number of filters	Filter	Pool	Number of filters	Filter	Pool
1	32	\(3 \times 3\)	–	32	\(3 \times 3\)	\(2 \times 2\)
2	32	\(3 \times 3\)	–	32	\(3 \times 3\)	\(2 \times 2\)
3	32	\(3 \times 3\)	\(2 \times 2\)	32	\(3 \times 3\)	\(2 \times 2\)

Dense layer	Number of neurons			Number of neurons
1	512			1024
2	512			1024
3	2			2

Padded vs. non-padded
	Deep padded			Padded/non-padded
Convolutional layer	Number of filters	Filter	Pool	Number of filters	Filter	Pool
1	128	\(3 \times 3\)	–	128	\(3 \times 3\)	–
2	128	\(3 \times 3\)	–	128	\(3 \times 3\)	–
3	128	\(3 \times 3\)	\(2 \times 2\)	128	\(3 \times 3\)	\(2 \times 2\)
4	128	\(3 \times 3\)	–	–	–	–
5	128	\(3 \times 3\)	–	–	–	–
6	128	\(3 \times 3\)	\(2 \times 2\)	–	–	–

Dense layer	Number of neurons			Number of neurons
1	512			1024
2	512			1024
3	2			2

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