Table 1.

The list of the tuned hyperparameters

Hyperparameter	Prob/pair/mixed matrix	One-hot matrix
Number of convolution layers	2, 4, 6	1
Kernel size for convolution	2, 3, 5	[8, 16], [4, 8, 12, 16], [2, 4, 6, 8, 10, 12, 14, 16]
		[2, 4, 6, 8, 10, 12, 14, 16]
		[2, 4, 6, 8, 10, 12, 14, 16]
Number of kernels (1st convolution layer)	16, 32, 64	64, 128, 256, 512
Number of kernels (2nd convolution layer)	32, 64, 128	not applicable
Pooling method	Max pooling, average pooling
Number of units (1st fully connected layer)	64, 128,256	128, 256, 512
Number of units (2nd fully connected layer)	32, 64, 128	not applicable
Learning algorithm	Adam, SGD
Dropout rate	0.7, 0.5