How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ‘edible’, ‘fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix‐Tensor Factorization (CMTF) problem.

中文翻译：

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Turbo-SMT：并行耦合稀疏矩阵张量因子分解及其应用。

我们如何在人脑对键入的单词做出反应时将它们的神经活动与这些术语的属性（例如“食用”，“适合”）联系起来？简而言之，我们想找到潜在的变量，这些变量可以共同解释大脑活动和行为反应。这是耦合矩阵-张量因数分解（CMTF）问题的许多设置之一。