1 code implementation • 19 May 2022 • Zhipeng Huang, Hadeel Soliman, Subhadeep Paul, Kevin S. Xu
Networks and temporal point processes serve as fundamental building blocks for modeling complex dynamic relational data in various domains.
1 code implementation • 2 May 2022 • Hadeel Soliman, Lingfei Zhao, Zhipeng Huang, Subhadeep Paul, Kevin S. Xu
The stochastic block model (SBM) is one of the most widely used generative models for network data.
1 code implementation • 27 Mar 2022 • Shanjukta Nath, Keith Warren, Subhadeep Paul
We investigate if there is a peer influence or role model effect on successful graduation from Therapeutic Communities (TCs).
no code implementations • 26 Oct 2019 • Selena Shuo Wang, Subhadeep Paul, Jessica Logan, Paul De Boeck
Using LSMH, we summarize the information from the social network and the item responses in a person-item joint latent space.
Applications Methodology
1 code implementation • NeurIPS 2020 • Makan Arastuie, Subhadeep Paul, Kevin S. Xu
In many application settings involving networks, such as messages between users of an on-line social network or transactions between traders in financial markets, the observed data consist of timestamped relational events, which form a continuous-time network.
no code implementations • 16 Dec 2018 • Subhadeep Paul, Olgica Milenkovic, Yuguo Chen
In particular, we prove non-asymptotic upper bounds on the misclustering error of spectral community detection for a SupSBM setting in which triangles or 3-uniform hyperedges are superimposed with undirected edges.
no code implementations • 24 Apr 2017 • Subhadeep Paul, Yuguo Chen
We consider the problem of estimating a consensus community structure by combining information from multiple layers of a multi-layer network using methods based on the spectral clustering or a low-rank matrix factorization.
no code implementations • 1 Aug 2016 • Subhadeep Paul, Yuguo Chen
Multi-layer networks are networks on a set of entities (nodes) with multiple types of relations (edges) among them where each type of relation/interaction is represented as a network layer.
Community Detection Methodology Social and Information Networks Physics and Society
no code implementations • 17 May 2016 • Subhadeep Paul, Yuguo Chen
We present a method based on the orthogonal symmetric non-negative matrix tri-factorization of the normalized Laplacian matrix for community detection in complex networks.
no code implementations • 8 Jun 2015 • Subhadeep Paul, Yuguo Chen
We derive consistency results for community assignments of the maximum likelihood estimators (MLEs) in both models where MLSBM is assumed to be the true model, and either the number of nodes or the number of types of edges or both grow.