253 citations · 721 across the 25 of their papers we have counts for
26 papers
Temporal Motif Participation Profiles for Analyzing Node Similarity in Temporal Networks
Maxwell C. Lee, Kevin S. Xu
Temporal networks consisting of timestamped interactions between a set of nodes provide a useful representation for analyzing complex networked systems that evolve over time. Beyon…
Spectral clustering for dependent community Hawkes process models of temporal networks
Lingfei Zhao, Hadeel Soliman, Kevin S. Xu +1
Temporal networks observed continuously over time through timestamped relational events data are commonly encountered in application settings including online social media communic…
A Hybrid Adjacency and Time-Based Data Structure for Analysis of Temporal Networks
Tanner Hilsabeck, Makan Arastuie, Kevin S. Xu
Dynamic or temporal networks enable representation of time-varying edges between nodes. Conventional adjacency-based data structures used for storing networks such as adjacency lis…
A Mutually Exciting Latent Space Hawkes Process Model for Continuous-time Networks
Zhipeng Huang, Hadeel Soliman, Subhadeep Paul +1
Networks and temporal point processes serve as fundamental building blocks for modeling complex dynamic relational data in various domains. We propose the latent space Hawkes (LSH)…
The Multivariate Community Hawkes Model for Dependent Relational Events in Continuous-time Networks
Hadeel Soliman, Lingfei Zhao, Zhipeng Huang +2
The stochastic block model (SBM) is one of the most widely used generative models for network data. Many continuous-time dynamic network models are built upon the same assumption a…
Learning User Embeddings from Temporal Social Media Data: A Survey
Fatema Hasan, Kevin S. Xu, James R. Foulds +1
User-generated data on social media contain rich information about who we are, what we like and how we make decisions. In this paper, we survey representative work on learning a co…
CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation
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…
Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks
Ruthwik R. Junuthula, Kevin S. Xu, Vijay K. Devabhaktuni
On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly stu…
DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks
Mahmudur Rahman, Tanay Kumar Saha, Mohammad Al Hasan +2
The temporal dynamics of a complex system such as a social network or a communication network can be studied by understanding the patterns of link appearance and disappearance over…
Personalized Degrees: Effects on Link Formation in Dynamic Networks from an Egocentric Perspective
Makan Arastuie, Kevin S. Xu
Understanding mechanisms driving link formation in dynamic social networks is a long-standing problem that has implications to understanding social structure as well as link predic…
The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks
Ruthwik R. Junuthula, Maysam Haghdan, Kevin S. Xu +1
We consider the problem of analyzing timestamped relational events between a set of entities, such as messages between users of an on-line social network. Such data are often analy…
Effects of Contact Network Models on Stochastic Epidemic Simulations
Rehan Ahmad, Kevin S. Xu
The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical…
Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity Data
Yuning Zhang, Maysam Haghdan, Kevin S. Xu
One of the main benefits of a wrist-worn computer is its ability to collect a variety of physiological data in a minimally intrusive manner. Among these data, electrodermal activit…
Block CUR: Decomposing Matrices using Groups of Columns
Urvashi Oswal, Swayambhoo Jain, Kevin S. Xu +1
A common problem in large-scale data analysis is to approximate a matrix using a combination of specifically sampled rows and columns, known as CUR decomposition. Unfortunately, in…
Evaluating Link Prediction Accuracy on Dynamic Networks with Added and Removed Edges
Ruthwik R. Junuthula, Kevin S. Xu, Vijay K. Devabhaktuni
The task of predicting future relationships in a social network, known as link prediction, has been studied extensively in the literature. Many link prediction methods have been pr…
A Compressed Sensing Based Decomposition of Electrodermal Activity Signals
Swayambhoo Jain, Urvashi Oswal, Kevin S. Xu +2
The measurement and analysis of Electrodermal Activity (EDA) offers applications in diverse areas ranging from market research, to seizure detection, to human stress analysis. Unfo…
Multi-criteria Similarity-based Anomaly Detection using Pareto Depth Analysis
Ko-Jen Hsiao, Kevin S. Xu, Jeff Calder +1
We consider the problem of identifying patterns in a data set that exhibit anomalous behavior, often referred to as anomaly detection. Similarity-based anomaly detection algorithms…
Stochastic Block Transition Models for Dynamic Networks
Kevin S. Xu
There has been great interest in recent years on statistical models for dynamic networks. In this paper, I propose a stochastic block transition model (SBTM) for dynamic networks t…
Consistent estimation of dynamic and multi-layer block models
Qiuyi Han, Kevin S. Xu, Edoardo M. Airoldi
Significant progress has been made recently on theoretical analysis of estimators for the stochastic block model (SBM). In this paper, we consider the multi-graph SBM, which serves…
Dynamic stochastic blockmodels for time-evolving social networks
Kevin S. Xu, Alfred O. Hero
Significant efforts have gone into the development of statistical models for analyzing data in the form of networks, such as social networks. Most existing work has focused on mode…
Predictability of social interactions
Kevin S. Xu
The ability to predict social interactions between people has profound applications including targeted marketing and prediction of information diffusion and disease propagation. Pr…
Revealing social networks of spammers through spectral clustering
Kevin S. Xu, Mark Kliger, Yilun Chen +2
To date, most studies on spam have focused only on the spamming phase of the spam cycle and have ignored the harvesting phase, which consists of the mass acquisition of email addre…
Dynamic stochastic blockmodels: Statistical models for time-evolving networks
Kevin S. Xu, Alfred O. Hero
Significant efforts have gone into the development of statistical models for analyzing data in the form of networks, such as social networks. Most existing work has focused on mode…
A Regularized Graph Layout Framework for Dynamic Network Visualization
Kevin S. Xu, Mark Kliger, Alfred O. Hero
Many real-world networks, including social and information networks, are dynamic structures that evolve over time. Such dynamic networks are typically visualized using a sequence o…