id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-020899-d6r4fr9r	Doinychko, Anastasiia	Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views	2020-03-17		.txt	text/plain	4666	244	56	In this paper, we present a conditional GAN with two generators and a common discriminator for multiview learning problems where observations have two views, but one of them may be missing for some of the training samples. We address the problem of multiview learning with Generative Adversarial Networks (GANs) in the case where some observations may have missing views without there being an external resource to complete them. We demonstrate that generated views allow to achieve state-of-the-art results on a subset of Reuters RCV1/RCV2 collections compared to multiview approaches that rely on Machine Translation (MT) for translating documents into languages in which their versions do not exist; before training the models. 3.2); -Achieve state-of-the art performance compared to multiview approaches that rely on external view generating functions on multilingual document classification; and which is another challenging application than image analysis which is the domain of choice for the design of new GAN models (Sect.	./cache/cord-020899-d6r4fr9r.txt	./txt/cord-020899-d6r4fr9r.txt