Are there any efficient (the forward speed is much faster than AlexNet) models that attain at least the same performance as AlexNet for image classification? • /r/MachineLearning

Are there any efficient (the forward speed is much faster than AlexNet) models that attain at least the same performance as AlexNet for image classification? Look up for model compression: there were discussions on this subreddit where people much more competent than me suggested literature for that. First paper that comes to mind: http://arxiv.org/abs/1504.04788 Check out SqueezeNet, although the focus here is more on the number of parameters/deployability rather than inference speed: http://arxiv.org/abs/1602.07360