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cs.LG2026
Cluster and then Embed: A Modular Approach for Visualization
Elizabeth Coda, Ery Arias-Castro, Gal Mishne
Dimensionality reduction methods such as t-SNE and UMAP are popular methods for visualizing data with a potential (latent) clustered structure. They are known to group data points…
math.ST2026
Confidence Bands for the Gradient Lines of a Density Function
Ery Arias-Castro, Wanli Qiao
We consider the problem of estimating the gradient ascent line of a density originating at a given point. Going beyond mere consistency, we establish a weak convergence result for…
stat.ML2026
Graph Max Shift: A Hill-Climbing Method for Graph Clustering
Ery Arias-Castro, Elizabeth Coda, Wanli Qiao
We present a method for graph clustering that is analogous to gradient ascent methods previously proposed for clustering points in space. The algorithm, which can be viewed as a ma…