Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling

1 code implementation • 20 Jan 2022 • Andrew Stolman, Caleb Levy, C. Seshadhri, Aneesh Sharma

In this work, we provide an empirical and theoretical analysis for the performance of a class of embeddings on the common task of pairwise community labeling.

Community Detection Graph Embedding +1

Randomized Algorithms for Scientific Computing (RASC)

no code implementations • 19 Apr 2021 • Aydin Buluc, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary Myers, Jelani Nelson, Juan M. Restrepo, C. Seshadhri, Draguna Vrabie, Brendt Wohlberg, Stephen J. Wright, Chao Yang, Peter Zwart

Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science.

The impossibility of low rank representations for triangle-rich complex networks

no code implementations • 27 Mar 2020 • C. Seshadhri, Aneesh Sharma, Andrew Stolman, Ashish Goel

The study of complex networks is a significant development in modern science, and has enriched the social sciences, biology, physics, and computer science.

Clustering Recommendation Systems

Local Algorithms for Hierarchical Dense Subgraph Discovery

2 code implementations • 2 Apr 2017 • Ahmet Erdem Sariyuce, C. Seshadhri, Ali Pinar

We present a framework of local algorithms to obtain the core, truss, and nucleus decompositions.

Social and Information Networks Data Structures and Algorithms

A Fast and Provable Method for Estimating Clique Counts Using Turán's Theorem

1 code implementation • 17 Nov 2016 • Shweta Jain, C. Seshadhri

Most methods used for triangle counting do not scale for large cliques, and existing algorithms require massive parallelism to be feasible.

Social and Information Networks Data Structures and Algorithms

Trigger detection for adaptive scientific workflows using percentile sampling

1 code implementation • 27 Jun 2015 • Janine C. Bennett, Ankit Bhagatwala, Jacqueline H. Chen, C. Seshadhri, Ali Pinar, Maher Salloum

Our results will be used for dynamic workflow decisions about data storage and mesh resolution in future combustion simulations.

Computational Engineering, Finance, and Science Distributed, Parallel, and Cluster Computing Mathematical Software

Community structure and scale-free collections of Erdös-Rényi graphs

1 code implementation • 15 Dec 2011 • C. Seshadhri, Tamara G. Kolda, Ali Pinar

Community structure plays a significant role in the analysis of social networks and similar graphs, yet this structure is little understood and not well captured by most models.

Social and Information Networks Physics and Society

Neighborhoods are good communities

1 code implementation • 30 Nov 2011 • David Gleich, C. Seshadhri

The communities of a social network are sets of vertices with more connections inside the set than outside.

Social and Information Networks Discrete Mathematics Data Structures and Algorithms Physics and Society