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Forward Looking Best-Response Multiplicative Weights Update Methods for Bilinear Zero-sum Games
Our work focuses on extra gradient learning algorithms for finding Nash equilibria in bilinear zero-sum games.
Cumulant GAN
In this paper, we propose a novel loss function for training Generative Adversarial Networks (GANs) aiming towards deeper theoretical understanding as well as improved stability and performance for the underlying optimization problem.
Training Generative Adversarial Networks with Weights
The impressive success of Generative Adversarial Networks (GANs) is often overshadowed by the difficulties in their training.
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