I love squeeze net. The idea is so incredibly simple. 3x3 convolutional kernels are really expensive in number of parameters with a high number of channels. Therefore apply a 1x1 CNN kernel to squeeze the number of channels before the 3x3. Then they do a ton of experiments to show that their proposed ratio of squeezing is right. Again this is exactly what a paper should do, love it!