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"NIPS Neural Information Processing Systems 8-11th December 2014, Montreal, Canada",,, "Paper ID:","1703" "Title:","How transferable are features in deep neural networks?" First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper aims to quantify the transferrability of features in deep neural networks, both in terms of the difference between source and target tasks and in terms of the depth of the features being transferred. To this end, the authors take an existing network (Krizhevsky et al. 2012), and performs generalization by fixing different layer depth and by transferring between different splits of the ImageNet dataset. I find the paper sufficiently interesting in the sense that, despite the many papers describing the success of feature transfer (e.g.