Venue: ICLR 2017 workshop

Reviews:

final_score: rating: 3: Clear rejection
review_content: The paper proposes an empirical evaluation of some unsupervised dimensionality reduction methods like t-sne, CAE… The paper does not introduce any novelty either any particular conclusion could be extracted from such us limited empirical evaluation over a limited data set from truck sensors. 
review_title: Empirical paper on dimensionality reduction

final_score: rating: 4: Ok but not good enough - rejection
review_content: The paper presents an application of convolutional autoencoders and t-SNE on engine data from Volvo trucks. Whilst this is a fine application of modern machine-learning techniques, I don't think it is suitable for the ICLR workshops: the goal of the workshop is to present new, not fully tested ideas. This submission does not present such ideas. I believe it would be more suitable for venues with a stronger focus on applications, such as KDD or IEEE Intelligent Transportation Systems.
review_title: Interesting application, but out-of-scope for ICLR Workshops

Decision: Reject