Venue: ICLR 2017 workshop

Reviews:

final_score: rating: 3: Clear rejection
review_content: This paper proposes to add output layers from middle layers to speed up inference. The paper showed that in the oracle condition speedup is possible. However, because of errors in making decisions on whether to pick the middle layer result, it's very unlikely that the proposed approach would work. There is no free lunch.
review_title: Not promising

final_score: rating: 3: Clear rejection
review_content: This work tries to speed up inference by taking a shortcut from the network. The paper shows that an accuracy increase is possible with such a shortcut. However, the way the accuracy is calculated for the proposed model is very unrealistic. The accuracy is calculated by only accepting the correct answers from the mid-level output. This way of an accuracy calculation will likely show an increase when you take the best out of the two networks. It is also known that in many cases shallower networks are less accurate than deeper models, so it is only normal that mid-level output gives some reasonable predictions but in average worse than the final output. I am not convinced about the future of this work, since there is no conducted experiments with promising results. 
review_title: No promising results

Decision: Reject