Cohen, Ruslan Salakhutdinov, Yann LeCunSupervising Unsupervised LearningOne major issue with Unsupervised learning is that there is no straightforward way to evaluate an algorithm’s performance..This makes it very hard to select an algorithm to tune hyperparameters or to evaluate performance.This article tries to overcome this issue using Meta Unsupervised Learning (MUL): a classifier is trained to decide which unsupervised model to use based on the characteristics of the dataset..But the JSD distance is not adapted to measure the distance between image distributions.In WGANs, the loss is modified so as to minimize the Wasserstein distance instead of the JSD distance..The results look promising as they surpass the baseline on the Moving MNIST dataset.Learning to Decompose and Disentangle Representations for Video Prediction — Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, Juan Carlos NieblesUnsupervised Learning of Artistic Styles with Archetypal Style AnalysisThis paper brings a new step towards unsupervised learning and Deep Learning interpretability..Especially it addresses the issue of style learning with root styles explanation and manipulation (here is a good introduction to style learning if you are new to this topics).The main idea is to project the input image into a low dimensional archetypes space where each base archetype is interpretable..Doing so, one is able to: attach some features to an image in an unsupervised manner (e.g. adding a tag about texture, style, age, etc. coming from the interpretation of the archetypes) and manipulate the coefficient over each style to influence and transfer style to the original image.Furthermore, the projection of the encoded image onto the archetypes is done with an optimization in the simplex in a two-sided manner: minimizing the distance of the images to their projections while enforcing the archetypes to be a linear combination of the images..So the archetypes are easily interpretable.In the end, it is possible to describe any image with base style ingredients, learning then a sort of a style dictionary..The style transfer can finally be precisely managed by the coefficients in the archetypes space.Unsupervised Learning of Artistic Styles with Archetypal Style Analysis — Daan Wynen, Cordelia Schmid, Julien MairalWant more articles like this one?. More details