activity
20152017
most citedClustering High Dimensional Dynamic Data Streams

17 citations · 25 across the 3 of their papers we have counts for

collaborators

6 papers

cs.DS2017

Approximating the Spectrum of a Graph

David Cohen-Steiner, Weihao Kong, Christian Sohler +1

The spectrum of a network or graph with adjacency matrix , consists of the eigenvalues of the normalized Laplacian . This set of eigenvalue…

cs.DS2017

Estimating Graph Parameters from Random Order Streams

Pan Peng, Christian Sohler

We develop a new algorithmic technique that allows to transfer some constant time approximation algorithms for general graphs into random order streaming algorithms. We illustrate…

cs.DS20178 cited

Testable Bounded Degree Graph Properties Are Random Order Streamable

Morteza Monemizadeh, S. Muthukrishnan, Pan Peng +1

We study which property testing and sublinear time algorithms can be transformed into graph streaming algorithms for random order streams. Our main result is that for bounded degre…

cs.DS201717 cited

Clustering High Dimensional Dynamic Data Streams

Vladimir Braverman, Gereon Frahling, Harry Lang +2

We present data streaming algorithms for the -median problem in high-dimensional dynamic geometric data streams, i.e. streams allowing both insertions and deletions of points fr…

cs.DS2016

Theoretical Analysis of the -Means Algorithm - A Survey

Johannes Blömer, Christiane Lammersen, Melanie Schmidt +1

The -means algorithm is one of the most widely used clustering heuristics. Despite its simplicity, analyzing its running time and quality of approximation is surprisingly diffic…

cs.DS2015

Testing Cluster Structure of Graphs

Artur Czumaj, Pan Peng, Christian Sohler

We study the problem of recognizing the cluster structure of a graph in the framework of property testing in the bounded degree model. Given a parameter , a -bounde…