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stat.ML2023
Manifold Learning with Sparse Regularised Optimal Transport
Stephen Zhang, Gilles Mordant, Tetsuya Matsumoto +1
Manifold learning is a central task in modern statistics and data science. Many datasets (cells, documents, images, molecules) can be represented as point clouds embedded in a high…
stat.ML2021
A unified framework for non-negative matrix and tensor factorisations with a smoothed Wasserstein loss
Stephen Y. Zhang
Non-negative matrix and tensor factorisations are a classical tool for finding low-dimensional representations of high-dimensional datasets. In applications such as imaging, datase…