436 citations · 1.4k across the 41 of their papers we have counts for
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cs.LG2018★ 436 cited
Federated Optimization in Heterogeneous Networks
Tian Li, Anit Kumar Sahu, Manzil Zaheer +3
Federated Learning is a distributed learning paradigm with two key challenges that differentiate it from traditional distributed optimization: (1) significant variability in terms…
cs.LG2018★ 57 cited
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn +1
Generative Adversarial Networks (GANs) are one of the most practical methods for learning data distributions. A popular GAN formulation is based on the use of Wasserstein distance…