11 citations · 66 across the 33 of their papers we have counts for
11 papers · 1 filter
Algorithms for metric learning via contrastive embeddings
Diego Ihara Centurion, Neshat Mohammadi, Anastasios Sidiropoulos
We study the problem of supervised learning a metric space under discriminative constraints. Given a universe and sets of similar and…
Sketching and Clustering Metric Measure Spaces
Facundo Mémoli, Anastasios Sidiropoulos, Kritika Singhal
Two important optimization problems in the analysis of geometric data sets are clustering and sketching. Here, clustering refers to the problem of partitioning some input metric me…
Algorithms for low-distortion embeddings into arbitrary 1-dimensional spaces
Timothy Carpenter, Fedor V. Fomin, Daniel Lokshtanov +2
We study the problem of finding a minimum-distortion embedding of the shortest path metric of an unweighted graph into a "simpler" metric . Computing such an embedding (exactly…
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…
Approximate Greedy Clustering and Distance Selection for Graph Metrics
David Eppstein, Sariel Har-Peled, Anastasios Sidiropoulos
In this paper, we consider two important problems defined on finite metric spaces, and provide efficient new algorithms and approximation schemes f…
How to Walk Your Dog in the Mountains with No Magic Leash
Sariel Har-Peled, Amir Nayyeri, Mohammad Salavatipour +1
We describe a -approximation algorithm for computing the homotopic \Frechet distance between two polygonal curves that lie on the boundary of a triangulated topological…