50 citations · 250 across the 16 of their papers we have counts for
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Group Invariant Spectral Embedding
Yeari Vigder, Paulina Hoyos, David Thong +3
Spectral embedding methods are widely used for dimensionality reduction and clustering of high-dimensional datasets with intrinsic low-dimensional structures. Although many dataset…
Manifold learning with arbitrary norms
Joe Kileel, Amit Moscovich, Nathan Zelesko +1
Manifold learning methods play a prominent role in nonlinear dimensionality reduction and other tasks involving high-dimensional data sets with low intrinsic dimensionality. Many o…
Product Manifold Learning
Sharon Zhang, Amit Moscovich, Amit Singer
We consider problems of dimensionality reduction and learning data representations for continuous spaces with two or more independent degrees of freedom. Such problems occur, for e…