Kernel Hyperalignment

2012-12-01 · NeurIPS 2012 12 · Alexander Lorbert, Peter J. Ramadge

We offer a regularized, kernel extension of the multi-set, orthogonal Procrustes problem, or hyperalignment. Our new method, called Kernel Hyperalignment, expands the scope of hyperalignment to include nonlinear measures of similarity and enables the alignment of multiple datasets with a large number of base features. With direct application to fMRI data analysis, kernel hyperalignment is well-suited for multi-subject alignment of large ROIs, including the entire cortex. We conducted experiments using real-world, multi-subject fMRI data.

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Deep Hyperalignment

2017-10-11 · NeurIPS 2017 12 · Muhammad Yousefnezhad, Daoqiang Zhang

This paper proposes Deep Hyperalignment (DHA) as a regularized, deep extension, scalable Hyperalignment (HA) method, which is well-suited for applying functional alignment to fMRI datasets with nonlinearity, high-dimensi…

Supervised Hyperalignment for multi-subject fMRI data alignment

2020-01-09 · Muhammad Yousefnezhad, Alessandro Selvitella, Liangxiu Han, Daoqiang Zhang

Hyperalignment has been widely employed in Multivariate Pattern (MVP) analysis to discover the cognitive states in the human brains based on multi-subject functional Magnetic Resonance Imaging (fMRI) datasets. Most of th…

Multi-Subject Fmri Data Alignment Time Series Time Series Analysis

Local Discriminant Hyperalignment for multi-subject fMRI data alignment

2016-11-25 · Muhammad Yousefnezhad, Daoqiang Zhang

Multivariate Pattern (MVP) classification can map different cognitive states to the brain tasks. One of the main challenges in MVP analysis is validating the generated results across subjects. However, analyzing multi-su…

Multi-Subject Fmri Data Alignment

Gradient Hyperalignment for multi-subject fMRI data alignment

2018-07-07 · Tonglin Xu, Muhammad Yousefnezhad, Daoqiang Zhang

Multi-subject fMRI data analysis is an interesting and challenging problem in human brain decoding studies. The inherent anatomical and functional variability across subjects make it necessary to do both anatomical and f…

Brain Decoding General Classification Multi-Subject Fmri Data Alignment

Unsupervised Hyperalignment for Multilingual Word Embeddings

2018-11-02 · Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin

We consider the problem of aligning continuous word representations, learned in multiple languages, to a common space. It was recently shown that, in the case of two languages, it is possible to learn such a mapping with…

Multilingual Word Embeddings Translation Word Embeddings Word Translation