Abstract: Distributed minimax optimization is essential for robust federated learning, offering resiliency against the variability in data distribution. Most previous works focus only on learning ...
Abstract: This paper investigates efficient algorithm for Markov Decision Processes (MDPs) through Linear programming (LP). Generally, solving large-scale MDPs via standard LP solvers faces ...
The quality of the latent space in visual tokenizers (e.g., VAEs) is crucial for modern generative models. However, the standard reconstruction-based training paradigm produces a latent space that is ...
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