[D] What is the best ML paper you read in 2017 and why? • r/MachineLearning

My pick for this year: "The Shattered Gradients Problem: If resnets are the answer, then what is the question?" Honorable mentions: 1. Poincaré Embeddings for Learning Hierarchical Representations (for elegance) 2. Inferring and Executing Programs for Visual Reasoning (for trying to tackle an important problem (not just VQA itself) the hard, but ultimately right way) 3. Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods (for bringing empirical joy to my heart)