Tag: nash
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Learning with the Nash-Sutcliffe loss
Learning with the Nash-Sutcliffe loss arXiv:2603.00968v1 Announce Type: new Abstract: The Nash-Sutcliffe efficiency ($text{NSE}$) is a widely used, positively oriented relative measure for evaluating forecasts across multiple time series. However, it lacks a decision-theoretic foundation for this purpose. To address this, we examine its negatively oriented counterpart, which we refer to as Nash-Sutcliffe loss, defined…
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Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression
Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression arXiv:2505.11143v1 Announce Type: new Abstract: Sparse linear regression is a fundamental tool in data analysis. However, traditional approaches often fall short when covariates exhibit structure or arise from heterogeneous sources. In biomedical applications, covariates may stem from distinct modalities or be structured according to an underlying graph.…