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Title: Co-manifold learning on data matrices Authors:  Eric Chi - North Carolina State University (United States) [presenting]
Gal Mishne - Yale University (United States)
Ronald Coifman - Yale University (United States)
Abstract: A new method is introduced for performing joint dimension reduction, or manifold learning, on the rows and columns of a data matrix. Our approach generalizes recent work on a convex formulation of the biclustering problem. Like convex biclustering, our co-manifold learning procedure possesses stability guarantees with respect to perturbations in the data. We illustrate how out method can identify coupled row and column geometries in simulated and real data examples.