The realm of machine learning is constantly transforming with innovative techniques aimed at enhancing model performance and tackling complex tasks. Among these advancements, fusion sets have emerged as a compelling concept, presenting a novel approach to merge diverse data sources and amplify the overall learning capabilities of algorithms. Fusion

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In this talk, I'll show that while in the non-parametric placing, the adversarial training challenge is comparable to a multimarginal best transportation dilemma that could be seen being a generalized Edition in the Wasserstein barycenter problem. The connection among these difficulties lets us to totally characterize the optimum adversarial approa