Reviews: Zero-shot Learning via Simultaneous Generating and Learning

Overview: The authors propose an original approach to zero-shot-learning by combining VAEs with EM for inferring the optimal unseen examples. The key idea is simultaneously generating examples of unseen classes and learning from them. The authors run a number of experiments which demonstrate that the proposed method shows competitive performance in a number of ZSL tasks. Quality: The work is generally of high quality. The experiments are clearly described, and the model specifications are detailed.