2 citations · 2 across the 4 of their papers we have counts for
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Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise
Boris Landa, Ronald R. Coifman, Yuval Kluger
A fundamental step in many data-analysis techniques is the construction of an affinity matrix describing similarities between data points. When the data points reside in Euclidean…
Co-manifold learning with missing data
Gal Mishne, Eric C. Chi, Ronald R. Coifman
Representation learning is typically applied to only one mode of a data matrix, either its rows or columns. Yet in many applications, there is an underlying geometry to both the ro…
Data-Driven Tree Transforms and Metrics
Gal Mishne, Ronen Talmon, Israel Cohen +2
We consider the analysis of high dimensional data given in the form of a matrix with columns consisting of observations and rows consisting of features. Often the data is such that…
Bigeometric Organization of Deep Nets
Alexander Cloninger, Ronald R. Coifman, Nicholas Downing +1
In this paper, we build an organization of high-dimensional datasets that cannot be cleanly embedded into a low-dimensional representation due to missing entries and a subset of th…