Jennifer Neville

According to our database1, Jennifer Neville authored at least 105 papers between 2002 and 2019.

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Bibliography

2019
Variational Random Function Model for Network Modeling.
IEEE Trans. Neural Netw. Learning Syst., 2019

Deep Lifetime Clustering.
CoRR, 2019

Community detection over a heterogeneous population of non-aligned networks.
CoRR, 2019

Social Reinforcement Learning to Combat Fake News Spread.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Stein-Papangelou Goodness-of-Fit Test for Point Processes.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

TransConv: Relationship Embedding in Social Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Tied Kronecker Product Graph Models to Capture Variance in Network Populations.
TKDD, 2018

Designing Size Consistent Statistics for Accurate Anomaly Detection in Dynamic Networks.
TKDD, 2018

Scalable and exact sampling method for probabilistic generative graph models.
Data Min. Knowl. Discov., 2018

The Indian Buffet Hawkes Process to Model Evolving Latent Influences.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Societal Impact of Data Science and Artificial Intelligence.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy.
Proceedings of the 35th International Conference on Machine Learning, 2018

Multi-level Hypothesis Testing for Populations of Heterogeneous Networks.
Proceedings of the IEEE International Conference on Data Mining, 2018

Nested CRP with Hawkes-Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Graphlet decomposition: framework, algorithms, and applications.
Knowl. Inf. Syst., 2017

Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls.
CoRR, 2017

Identifying User Survival Types via Clustering of Censored Social Network Data.
CoRR, 2017

Decoupling Homophily and Reciprocity with Latent Space Network Models.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Unified Representation and Lifted Sampling for Generative Models of Social Networks.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Should We Be Confident in Peer Effects Estimated From Social Network Crawls?
Proceedings of the Eleventh International Conference on Web and Social Media, 2017

How to Exploit Relationships to Improve Predictions.
Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval, 2017

Deep Collective Inference.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Size-Consistent Statistics for Anomaly Detection in Dynamic Networks.
CoRR, 2016

Combining Gradient Boosting Machines with Collective Inference to Predict Continuous Values.
CoRR, 2016

Better Together: Combining Language and Social Interactions into a Shared Representation.
Proceedings of TextGraphs@NAACL-HLT 2016: the 10th Workshop on Graph-based Methods for Natural Language Processing, 2016

Sampling of Attributed Networks from Hierarchical Generative Models.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015
Using Bayesian Network Representations for Effective Sampling from Generative Network Models.
CoRR, 2015

Fast Parallel Graphlet Counting for Large Networks.
CoRR, 2015

Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks.
Proceedings of the 24th International Conference on World Wide Web, 2015

Analyzing the Transferability of Collective Inference Models Across Networks.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

Efficient Graphlet Counting for Large Networks.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Incorporating Assortativity and Degree Dependence into Scalable Network Models.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Signal Processing for Big Data [From the Guest Editors].
IEEE Signal Process. Mag., 2014

Anomaly Detection in Dynamic Networks of Varying Size.
CoRR, 2014

Learning the Latent State Space of Time-Varying Graphs.
CoRR, 2014

Attributed graph models: modeling network structure with correlated attributes.
Proceedings of the 23rd International World Wide Web Conference, 2014

Assortativity in Chung Lu Random Graph Models.
Proceedings of the 8th Workshop on Social Network Mining and Analysis, 2014

Graph sample and hold: a framework for big-graph analytics.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

A Scalable Method for Exact Sampling from Kronecker Family Models.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2013
Network Sampling: From Static to Streaming Graphs.
TKDD, 2013

LBSN 2012 workshop report: the Fifth ACM SIGSPATIAL International Workshop on Location-Based Social Networks (Redondo Beach, California - November 6, 2012).
SIGSPATIAL Special, 2013

Collective inference for network data with copula latent markov networks.
Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Modeling dynamic behavior in large evolving graphs.
Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Learning mixed kronecker product graph models with simulated method of moments.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Network Hypothesis Testing Using Mixed Kronecker Product Graph Models.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Correcting evaluation bias of relational classifiers with network cross validation.
Knowl. Inf. Syst., 2012

Transforming Graph Data for Statistical Relational Learning.
J. Artif. Intell. Res., 2012

Dynamic Behavioral Mixed-Membership Model for Large Evolving Networks
CoRR, 2012

Transforming Graph Representations for Statistical Relational Learning
CoRR, 2012

Fast Generation of Large Scale Social Networks with Clustering
CoRR, 2012

Role-dynamics: fast mining of large dynamic networks.
Proceedings of the 21st World Wide Web Conference, 2012

Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures.
Proceedings of the 2012 International Conference on Privacy, 2012

The Impact of Communication Structure and Interpersonal Dependencies on Distributed Teams.
Proceedings of the 2012 International Conference on Privacy, 2012

Time-Evolving Relational Classification and Ensemble Methods.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2012

Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems.
Proceedings of the 9th USENIX Symposium on Networked Systems Design and Implementation, 2012

Space-efficient sampling from social activity streams.
Proceedings of the 1st International Workshop on Big Data, 2012

Network Sampling Designs for Relational Classification.
Proceedings of the Sixth International Conference on Weblogs and Social Media, 2012

An analysis of how ensembles of collective classifiers improve predictions in graphs.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
Guided data repair.
PVLDB, 2011

Introduction to the special issue on mining and learning with graphs.
Machine Learning, 2011

Relational Learning with One Network: An Asymptotic Analysis.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Representations and Ensemble Methods for Dynamic Relational Classification
CoRR, 2011

Prediction models for long-term Internet prefix availability.
Computer Networks, 2011

Gender demographics trends and changes in U.S. CS departments.
Commun. ACM, 2011

Correcting Bias in Statistical Tests for Network Classifier Evaluation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure.
Proceedings of the Fifth International Conference on Weblogs and Social Media, 2011

Relational Active Learning for Joint Collective Classification Models.
Proceedings of the 28th International Conference on Machine Learning, 2011

Understanding Propagation Error and Its Effect on Collective Classification.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Across-Model Collective Ensemble Classification.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Modeling relationship strength in online social networks.
Proceedings of the 19th International Conference on World Wide Web, 2010

Randomization tests for distinguishing social influence and homophily effects.
Proceedings of the 19th International Conference on World Wide Web, 2010

GDR: a system for guided data repair.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2010

ERACER: a database approach for statistical inference and data cleaning.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2010

Multi-network fusion for collective inference.
Proceedings of the Eighth Workshop on Mining and Learning with Graphs, 2010

Time-based sampling of social network activity graphs.
Proceedings of the Eighth Workshop on Mining and Learning with Graphs, 2010

Modeling the evolution of discussion topics and communication to improve relational classification.
Proceedings of the 3rd Workshop on Social Network Mining and Analysis, 2010

Predicting Prefix Availability in the Internet.
Proceedings of the INFOCOM 2010. 29th IEEE International Conference on Computer Communications, 2010

Ranking for data repairs.
Proceedings of the Workshops Proceedings of the 26th International Conference on Data Engineering, 2010

2009
Using Transactional Information to Predict Link Strength in Online Social Networks.
Proceedings of the Third International Conference on Weblogs and Social Media, 2009

Evaluating Statistical Tests for Within-Network Classifiers of Relational Data.
Proceedings of the ICDM 2009, 2009

2008
A bias/variance decomposition for models using collective inference.
Machine Learning, 2008

AI's 10 to Watch.
IEEE Intelligent Systems, 2008

Pseudolikelihood EM for Within-network Relational Learning.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Temporal-Relational Classifiers for Prediction in Evolving Domains.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Database Support for Probabilistic Attributes and Tuples.
Proceedings of the 24th International Conference on Data Engineering, 2008

2007
Relational Dependency Networks.
J. Mach. Learn. Res., 2007

Bias/Variance Analysis for Relational Domains.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

2005
Using relational knowledge discovery to prevent securities fraud.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Leveraging Relational Autocorrelation with Latent Group Models.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Structure Learning for Statistical Relational Models.
Proceedings of the Proceedings, 2005

2004
Why collective inference improves relational classification.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Dependency Networks for Relational Data.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

2003
Exploiting relational structure to understand publication patterns in high-energy physics.
SIGKDD Explorations, 2003

Learning relational probability trees.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Avoiding Bias when Aggregating Relational Data with Degree Disparity.
Proceedings of the Machine Learning, 2003

Simple Estimators for Relational Bayesian Classifiers.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

2002
Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning.
Proceedings of the Machine Learning, 2002


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