High-dimensional datasets arise across disciplines from genomics and neuroimaging to finance and social science. As the number of variables grows, statistical inference and predictive modelling become ...

Dimensionality reduction is a fundamental task in modern data science. Several projection methods specifically tailored to take into account the non-linearity of the data via local embeddings have ...

Statisticians from the National University of Singapore (NUS) have introduced a new technique that accurately describes high-dimensional data using lower-dimensional smooth structures. This innovation ...