Jennifer Neville

Publications / By Date / By Type /

20132012201120102009200820072006200520042003200220012000

2013

N. Ahmed, J. Neville, and R. Kompella. Network Sampling: From Static to Streaming Graphs. ACM Transactions on Knowledge Discovery from Data, 2013. [PDF] 

J. Pfeiffer III, J. Neville, and P. Bennett. Combining Active Sampling with Parameter Estimation and Prediction in Single Networks. In Proceedings of the Structured Learning: Inferring Graphs from Structured and Unstructured Inputs Workshop, ICML, 2013. [PDF] 

S. Moreno, J. Neville, and S. Kirshner. Learning Mixed Kronecker Product Graph Models with Simulated Method of Moments. In Proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2013. [PDF] 

S. Moreno and J. Neville. Network Hypothesis Testing Using Mixed Kronecker Product Graph Models. In Proceedings of the 13th IEEE International Conference on Data Mining, 2013. [PDF] 

R. Rossi, B. Gallagher, J. Neville, and K. Henderson. Modeling Dynamic Behavior in Large Evolving Graphs. In Proceedings of the 6th ACM International Conference on Web Search and Data Mining, 2013. [PDF] 

R. Xiang and J. Neville. Collective Inference for Network Data with Copula Latent Markov Networks. In Proceedings of the 6th ACM International Conference on Web Search and Data Mining, 2013. [PDF] 



2012

N. Ahmed, J. Neville, and R. Kompella. Network Sampling Designs for Relational Classification. In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media, 2012. [PDF] 

N. Ahmed, J. Neville, and R. Kompella. Space-Efficient Sampling from Social Activity Streams. In Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining, KDD, 2012. [PDF] 

J. Bates, J. Neville, and J. Tyler. Using Latent Communication Styles to Predict Individual Characteristics. In Proceedings of the 3rd Workshop on Social Media Analytics, KDD, 2012. [PDF] 

H. Eldardiry and J. Neville. An Analysis of How Ensembles of Collective Classifiers Improve Predictions in Graphs. In Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012. [PDF] 

T. La Fond, D. Roberts, J. Neville, J. Tyler, and S. Connaughton. The Impact of Communication Structure and Interpersonal Dependencies on Distributed Teams. In Proceedings of the 4th ASE/IEEE International Conference on Social Computing, 2012. [PDF] 

J. Pfeiffer III, J. Neville, and P. Bennett. Active Sampling of Networks. In Proceedings of the 10th Workshop on Mining and Learning with Graphs, ICML, 2012. [PDF] 

J. Pfeiffer III, T. La Fond, S. Moreno, and J. Neville. Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures. In Proceedings of the 4th ASE/IEEE International Conference on Social Computing, 2012. [PDF] 

K. Nagaraj, C. Killian, and J. Neville. Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems. In Proceedings of the 9th USENIX Symposium on Networked Systems Design and Implementation, 2012. [PDF] 

J. Neville, B. Gallagher, T. Eliassi-Rad, and T. Wang. Correcting Evaluation Bias of Relational Classifiers with Network Cross Validation. Knowledge and Information Systems, 30:31–55, 2012. [PDF] 

R. Rossi and J. Neville. Time-Evolving Relational Classification and Ensemble Methods. In Proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2012. [PDF] 

R. Rossi, B. Gallagher, J. Neville, and K. Henderson. Role-Dynamics: Fast Mining of Large Dynamic Networks. In Proceedings of the 1st Workshop on Large Scale Network Analysis, WWW, 2012. [PDF] 

R. Rossi, L. McDowell, D. Aha, and J. Neville. Transforming Graph Data for Statistical Relational Learning. Journal of Artificial Intelligence Research, 45:363–441, 2012. [PDF] 

R. Xiang and J. Neville. On the Mismatch Between Learning and Inference for Single Network Domains. In Proceedings of the ICML Workshop on Inferning: Interactions between Inference and Learning, 2012. [PDF] 



2011

N. Ahmed, and J. Neville, and R. Kompella. Network Sampling via Edge-based Node Selection with Graph Induction. Technical Report 11-016, Dept of Computer Science, Purdue University, 2011. [PDF] 

D. Baumann, S. Hambrusch, and J. Neville. Gender demographics trends and changes in U.S. CS departments. Commun. ACM, 54:38–42, 2011. [PDF] 

H. Eldardiry and J. Neville. Across-Model Collective Ensemble Classification. In Proceedings of the 25th AAAI Conference on Artificial Intelligence, 2011. [PDF] 

J. Pfeiffer III and J. Neville. Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. In Proceedings of the 5th International AAAI Conference on Weblogs and Social Media, 2011. [PDF] 

A. Kuwadekar and J. Neville. Relational Active Learning for Joint Collective Classification Models. In Proceedings of the 28th International Conference on Machine Learning, 2011. [PDF] 

T. Wang, J. Neville, B. Gallagher, and T. Eliassi-Rad. Correcting Bias in Statistical Tests for Network Classifier Evaluation. In Proceedings of the 21st European Conference on Machine Learning, 2011. [PDF] 

R. Xiang and J. Neville. Relational Learning with One Network: An Asymptotic Analysis. In Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTAT), 2011. [PDF] 

R. Xiang and J. Neville. Understanding Propagation Error and Its Effect on Collective Classification. In Proceedings of the 11th IEEE International Conference on Data Mining, 2011. [PDF] 

M. Yakout, A. Elmagarmid, J. Neville, M. Ouzzani, and I. Ilyas. Guided Data Repair. Proceedings of the VLDB Endowment, 2011. [PDF] 



2010

N. Ahmed, F. Berchmans, J. Neville, and R. Kompella. Time-Based Sampling of Social Network Activity Graphs. In Proceedings of the 8th Workshop on Mining and Learning with Graphs, 2010. [PDF] 

N. Ahmed, J. Neville, and R. Kompella. Reconsidering the Foundations of Network Sampling. In Proceedings of the 2nd Workshop on Information in Networks, 2010. [PDF] 

H. Eldardiry and J. Neville. Multi-Network Fusion for Collective Inference. In Proceedings of the 8th Workshop on Mining and Learning with Graphs, 2010. [PDF] 

J. Pfeiffer III and J. Neville. Probabilistic Paths and Centrality in Time. In Proceedings of the 4th SNA-KDD Workshop, KDD, 2010. [PDF] 

R. Khosla, S. Fahmy, C. Hu, and J. Neville. Predicting Prex Availability in the Internet. In Proceedings of the 29th IEEE Conference on Computer Communications (INFOCOM) Mini-Conference, 2010. [PDF] 

R. Khosla, S. Fahmy, C. Hu, and J. Neville. Prediction models for long-term Internet prefix availability. Computer Networks, 2010. [PDF] 

A. Kuwadekar and J. Neville. Combining Semi-supervised Learning and Relational Resampling for Active Learning in Network Domains. In Proceedings of the Budgeted Learning Workshop, ICML, 2010. [PDF] 

T. LaFond and J. Neville. Randomization tests for distinguishing social influence and homophily effects. In Proceedings of the International World Wide Web Conference (WWW), 2010. [PDF] 

C. Mayfield, J. Neville, and S. Prabhakar. ERACER: A Database Approach for Statistical Inference and Data Cleaning. In Proceedings of the 2010 ACM SIGMOD Conference, 2010. [PDF] 

S. Moreno, S. Kirshner, J. Neville, and S.V.N. Vishwanathan. Tied Kronecker Product Graph Models to Capture Variance in Network Populations. In Proceedings of the 48th Annual Allerton Conference on Communications, Controland Computing, 2010. [PDF] 

S. Moreno, J. Neville, S. Kirshner, and S.V.N. Vishwanathan. Modeling the Variance of Network Populations with Mixed Kronecker Product Graph Models. In Proceedings of the 2010 NIPS Workshop on Networks Across Disciplines: Theory and Applications, 2010. [PDF] 

R. Rossi and J. Neville. Modeling the Evolution of Discussion Topics and Communication to Improve Relational Classification. In Proceedings of the 1st Workshop on Social Media Analytics, KDD, 2010. [PDF] 

R. Xiang, J. Neville, and M. Rogati. Modeling Relationship Strength in Online Social Networks. In Proceedings of the International World Wide Web Conference (WWW), 2010. [PDF] 

M. Yakout, A. Elmagarmid, and J. Neville. Ranking for Data Repairs. In Proceedings of the 4th International Workshop on Ranking in Databases, ICDE, 2010. [PDF] 

M. Yakout, A. Elmagarmid, J. Neville, and M. Ouzzani. GDR: A System for Guided Data Repair. In Proceedings of the 2010 International Conference on Management of Data (SIGMOD), 2010. [PDF] 



2009

I. Kahanda and J. Neville. Using Transactional Information to Predict Link Strength in Online Social Networks. In Proceedings of the 3rd International AAAI Conference on Weblogs and Social Media, 2009. [PDF] 

S. Moreno and J. Neville. An Investigation of the Distributional Characteristics of Generative Graph Models. In Proceedings of the 1st Workshop on Information in Networks, 2009. [PDF] 

J. Neville, B. Gallagher, and T. Eliassi-Rad. Evaluating Statistical Tests for Within-Network Classifiers of Relational Data. In Proceedings of the 9th IEEE International Conference on Data Mining, 2009. [PDF] 

R. Xiang, J. Neville, and M. Rogati. Modeling Relationship Strength in Online Social Networks. In Proceedings of the NIPS Workshop on Analyzing Networks and Learning With Graphs, 2009. [PDF] 



2008

P. Angin and J. Neville. A Shrinkage Approach for Modeling Non-Stationary Relational Autocorrelation,. In Proceedings of the 2nd SNA Workshop, 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2008. [PDF] 

P. Angin and J. Neville. A Shrinkage Approach for Modeling Non-Stationary Relational Autocorrelation. In Proceedings of the 8th IEEE International Conference on Data Mining, 2008. [PDF] 

H. Eldardiry and J. Neville. A Resampling Technique for Relational Data Graphs. In Proceedings of the 2nd SNA Workshop, 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2008. [PDF] 

J. Neville and D. Jensen. A Bias/Variance Decomposition for Models Using Collective Inference. Machine Learning Journal, 2008. [PDF] 

U. Sharan and J. Neville. Temporal-Relational Classifiers for Prediction in Evolving Domains. In Proceedings of the 8th IEEE International Conference on Data Mining, 2008. [PDF] 

S. Singh, C. Mayfield, R. Shah, S. Prabhakar, S. Hambrusch, J. Neville, and R. Cheng. Database support for probabilistic attributes and tuples. In Proceedings of the 24th International Conference on Data Engineering, 2008. [PDF] 

R. Xiang and J. Neville. Pseudolikelihood EM for Within-Network Relational Learning,. In Proceedings of the 2nd SNA Workshop, 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2008. [PDF] 

R. Xiang and J. Neville. Pseudolikelihood EM for Within-Network Relational Learning. In Proceedings of the 8th IEEE International Conference on Data Mining, 2008. [PDF] 



2007

J. Neville and D. Jensen. Relational Dependency Networks. In L. Getoor and B. Taskar, editors, Introduction to Statistical Relational Learning, 2007. [PDF] 

J. Neville and D. Jensen. Relational Dependency Networks. Journal of Machine Learning Research, 2007. [PDF] 

J. Neville and D. Jensen. Bias-Variance Analysis for Relational Domains. In Proceedings of the 17th International Conference on Inductive Logic Programming, 2007. [PDF] 

U. Sharan and J. Neville. Exploiting Time-Varying Relationships in Statistical Relational Models. In Proceedings of the 1st SNA-KDD Workshop, 13th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2007. [PDF] 



2006

J. Neville. Statistical Models and Analysis Techniques for Learning in Relational Data. Ph.D. Thesis, University of Massachusetts Amherst, 2006. [PDF] 



2005

J. Neville and D. Jensen. Leveraging Relational Autocorrelation with Latent Group Models. In Proceedings of the 5th IEEE International Conference on Data Mining, pp. 322–329, 2005. [PDF] 

J. Neville, O. Simsek, D. Jensen, J. Komoroske, K. Palmer, and H. Goldberg. Using Relational Knowledge Discovery to Prevent Securities Fraud. In Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 449–458, 2005. [PDF] 



2004

D. Jensen, J. Neville, and B. Gallagher. Why Collective Inference Improves Relational Classification. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 593–598, 2004. [PDF] 

J. Neville and D. Jensen. Dependency Networks for Relational Data. In Proceedings of the 4th IEEE International Conference on Data Mining, pp. 170–177, 2004. [PDF] 

J. Neville, M. Adler, and D. Jensen. Spectral Clustering with Links and Attributes. Technical Report 04-42, Dept of Computer Science, University of Massachusetts Amherst, 2004. [PDF] 

J. Neville, O. Simsek, and D. Jensen. Autocorrelation and Relational Learning: Challenges and Opportunities. In Proceedings of the Workshop on Statistical Relational Learning, 21st International Conference on Machine Learning, 2004. [PDF] 



2003

D. Jensen, J. Neville, and M. Rattigan. Randomization Tests for Relational Learning. Technical Report 03-05, Dept of Computer Science, University of Massachusetts Amherst, 2003. [PDF] 

D. Jensen, J. Neville, and M. Hay. Avoiding bias when aggregating relational data with degree disparity. In Proceedings of the 20th International Conference on Machine Learning, pp. 274–281, 2003. [PDF] 

A. McGovern, L. Friedland, M. Hay, B. Gallagher, A. Fast, J. Neville, and D. Jensen. Exploiting Relational Structure to Understand Publication Patterns in High-Energy Physics. SIGKDD Explorations, 5(2):165–172, 2003. [PDF] 

J. Neville and D. Jensen. Collective Classification with Relational Dependency Networks. In Proceedings of the 2nd Multi-Relational Data Mining Workshop, 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 77–91, 2003. [PDF] 

J. Neville, D. Jensen, and B. Gallagher. Simple Estimators for Relational Bayesian Classifers. In Proceedings of the 3rd IEEE International Conference on Data Mining, pp. 609–612, 2003. [PDF] 

J. Neville, D. Jensen, L. Friedland, and M. Hay. Learning Relational Probability Trees. In Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 625–630, 2003. [PDF] 

J. Neville, M. Rattigan, and D. Jensen. Statistical Relational Learning: Four Claims and a Survey. In Proceedings of the Workshop on Learning Statistical Models from Relational Data, 18th International Joint Conference on Artificial Intelligence, 2003. [PDF] 

J. Neville, M. Adler, and D. Jensen. Clustering Relational Data Using Attribute and Link Information. In Proceedings of the Text Mining and Link Analysis Workshop, 18th International Joint Conference on Artificial Intelligence, 2003. [PDF] 



2002

D. Jensen and J. Neville. Schemas and Models. In Proceedings of the Multi-Relational Data Mining Workshop, 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002. [PDF] 

D. Jensen and J. Neville. Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. In Proceedings of the 19th International Conference on Machine Learning, pp. 259–266, 2002. [PDF] 

D. Jensen and J. Neville. Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. In Proceedings of the 12th International Conference on Inductive Logic Programming, pp. 101–116, 2002. [PDF] 

D. Jensen and J. Neville. Data Mining in Social Networks. In National Academy of Sciences Symposium on Dynamic Social Network Analysis, 2002. [PDF] 

J. Neville and D. Jensen. Supporting Relational Knowledge Discovery: Lessons in Architecture and Algorithm Design. In Proceedings of the Data Mining Lessons Learned Workshop, 19th International Conference on Machine Learning, pp. 57–64, 2002. [PDF] 



2001

D. Jensen and J. Neville. Correlation and Sampling in Relational Data Mining. In Proceedings of the 33rd Symposium on the Interface of Computing Science and Statistics, 2001. [PDF] 



2000

J. Neville and D. Jensen. Iterative Classification in Relational Data. In Proceedings of the Workshop on Statistical Relational Learning, 17th National Conference on Artificial Intelligence, pp. 42–49, 2000. [PDF] 



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