Neville, Jennifer - Departments of Computer Sciences & Statistics, Purdue University

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Neville, Jennifer - Departments of Computer Sciences & Statistics, Purdue University

STATISTICAL MODELS AND ANALYSIS TECHNIQUES FOR LEARNING IN RELATIONAL DATA
Journal of Machine Learning Research 8 (2007) 653-692 Submitted 9/05; Revised 9/06; Published 3/07 Relational Dependency Networks
Relational Active Learning for Joint Collective Classification Models Ankit Kuwadekar akuwadek@purdue.edu
Relational Learning with One Network: An Asymptotic Analysis Rongjing Xiang Jennifer Neville
Randomization Tests for Distinguishing Social Influence and Homophily Effects
ERACER: A Database Approach for Statistical Inference and Data Cleaning
Using Transactional Information to Predict Link Strength in Online Social Networks
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data Jennifer Neville
A Shrinkage Approach for Modeling Non-Stationary Relational Autocorrelation
Database Support for Probabilistic Attributes and Tuples
Pseudolikelihood EM for Within-Network Relational Learning Rongjing Xiang
Probabilistic Paths and Centrality in Time Joseph J. Pfeiffer, III
A Shrinkage Approach for Modeling Non-Stationary Relational Autocorrelation
A Resampling Technique for Relational Data Graphs
1 Relational Dependency Networks Jennifer Neville and David Jensen
Spectral Clustering with Links and Attributes Jennifer Neville
Journal of Machine Learning Research Submitted 1/2005; Revised 6/2006; forthcoming Classification in Networked Data
Combining Semi-supervised Learning and Relational Resampling for Active Learning in Network Domains
Modeling the Evolution of Discussion Topics and Communication to Improve Relational Classification
Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure
Exploiting Time-Varying Relationships in Statistical Relational Models
A Bias/Variance Decomposition for Models Using Collective Inference
Pseudolikelihood EM for Within-Network Relational Learning
Reconsidering the Foundations of Network Sampling Nesreen K. Ahmed, Jennifer Neville, Ramana Kompella
Multi-Network Fusion for Collective Inference Hoda Eldardiry and Jennifer Neville
An Investigation of the Distributional Characteristics of Generative Graph Models
Predicting Prefix Availability in the Internet Ravish Khosla, Sonia Fahmy, Y. Charlie Hu, Jennifer Neville
Temporal-Relational Classifiers for Prediction in Evolving Domains Umang Sharan
Across-Model Collective Ensemble Classification Hoda Eldardiry and Jennifer Neville
Modeling Relationship Strength in Online Social Networks
Correcting Bias in Statistical Tests for Network Classifier Evaluation
Understanding Propagation Error and Its Effect on Collective Classification