• By Date • By Type •

• Journal • Conference • Workshop • Thesis • Chapter • Tech Report •

Journal

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

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

Conference

I. Kahanda and J. Neville. Using Transactional Information to Predict Link Strength in Online Social Networks. In Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, 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] 

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] 

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 8th IEEE International Conference on Data Mining, 2008. [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] 

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] 

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] 

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] 

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] 

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] 

Workshop

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

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] 

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] 

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] 

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] 

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] 

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, 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] 

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. 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] 

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] 

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] 

Thesis

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

Chapter

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

Tech Report

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] 

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] 

Generated by bib2html.pl on Mon Nov 16, 2009 11:52:29