21 citations · 70 across the 9 of their papers we have counts for
13 papers
Declutter and Resample: Towards parameter free denoising
Mickaël Buchet, Tamal K. Dey, Jiayuan Wang +1
In many data analysis applications the following scenario is commonplace: we are given a point set that is supposed to sample a hidden ground truth in a metric space, but it go…
Computing the Gromov-Hausdorff Distance for Metric Trees
Pankaj K. Agarwal, Kyle Fox, Abhinandan Nath +2
The Gromov-Hausdorff (GH) distance is a natural way to measure distance between two metric spaces. We prove that it is -hard to approximate the Gromov-Hausdorff distan…
Metric embedding with outliers
Anastasios Sidiropoulos, Yusu Wang
We initiate the study of metric embeddings with \emph{outliers}. Given some metric space we wish to find a small set of outlier points and either an isometric…
Mutiscale Mapper: A Framework for Topological Summarization of Data and Maps
Tamal K. Dey, Facundo Memoli, Yusu Wang
Summarizing topological information from datasets and maps defined on them is a central theme in topological data analysis. \textsf{Mapper}, a tool for such summarization, takes as…
Comparing Graphs via Persistence Distortion
Tamal K. Dey, Dayu Shi, Yusu Wang
Metric graphs are ubiquitous in science and engineering. For example, many data are drawn from hidden spaces that are graph-like, such as the cosmic web. A metric graph offers one…
Strong Equivalence of the Interleaving and Functional Distortion Metrics for Reeb Graphs
Ulrich Bauer, Elizabeth Munch, Yusu Wang
The Reeb graph is a construction that studies a topological space through the lens of a real valued function. It has widely been used in applications, however its use on real data…