Tony Wirth

Correlation Clustering in Data Streams

Kook Jin Ahn, Graham Cormode, Sudipto Guha, Andrew McGregor, Anthony Wirth

Journal article  |  2021  |  ALGORITHMICA

Clustering is a fundamental tool for analyzing large data sets. A rich body of work has been devoted to designing data-stream algo..

Dynamic Structural Clustering on Graphs

B Ruan, J Gan, H Wu, A Wirth

Conference Proceedings  |  2021  |  Proceedings of the ACM SIGMOD International Conference on Management of Data

\em Structural Clustering ($\strclu$) is one of the most popular graph clustering paradigms. In this paper, we consider &#..

Recency queries with succinct representation

WL Holland, A Wirth, J Zobel

Conference Proceedings  |  2020  |  Leibniz International Proceedings in Informatics, LIPIcs

Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs

Nate Veldt, Anthony Wirth, David F Gleich

Conference Proceedings  |  2020  |  Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Motivated by applications in community detection and dense subgraph discovery, we consider new clustering objectives in hypergraph..

Graph clustering in all parameter regimes

Junhao Gan, DF Gleich, N Veldt, Anthony Wirth, Xin Zhang

Conference Proceedings  |  2020  |  Leibniz International Proceedings in Informatics, LIPIcs

Resolution parameters in graph clustering control the size and structure of clusters formed by solving a parametric objective func..

Result-sensitive binary search with noisy information

NS Epa, J Gan, A Wirth

Conference Proceedings  |  2019  |  Leibniz International Proceedings in Informatics, LIPIcs

Metric-Constrained Optimization for Graph Clustering Algorithms

Nate Veldt, David F Gleich, Anthony Wirth, James Saunderson

Journal article  |  2019  |  SIAM Journal on Mathematics of Data Science

We outline a new approach for solving linear programming relaxations of NP-hard graph clustering problems that enforce triangle in..

Learning resolution parameters for graph clustering

N Veldt, DF Gleich, A Wirth

Conference Proceedings  |  2019

Finding clusters of well-connected nodes in a graph is an extensively studied problem in graph-based data analysis. Because of its..

Correlation clustering generalized

DF Gleich, N Veldt, A Wirth

Conference Proceedings  |  2018  |  Proceedings of the 29th International Symposium on Algorithms and Computation

We present new results for LambdaCC and MotifCC, two recently introduced variants of the well-studied correlation clustering probl..

A Correlation Clustering Framework for Community Detection

Nate Veldt, David F Gleich, Anthony Wirth

Conference Proceedings  |  2018

Graph clustering, or community detection, is the task of identifying groups of closely related objects in a large network. In this..