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ORCIDJennifer Neville
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- affiliation: Purdue University, West Lafayette, USA
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2020 – today
- 2024
[c97]Ying-Chun Lin, Jennifer Neville, Jack W. Stokes, Longqi Yang, Tara Safavi, Mengting Wan, Scott Counts, Siddharth Suri, Reid Andersen, Xiaofeng Xu, Deepak Gupta, Sujay Kumar Jauhar, Xia Song, Georg Buscher, Saurabh Tiwary, Brent J. Hecht, Jaime Teevan:
Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models. ACL (1) 2024: 11100-11115- [c96]Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, Tara Safavi:
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. ACL (Findings) 2024: 14996-15014 - [c95]Tobias Schnabel, Jennifer Neville:
Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. EMNLP (Findings) 2024: 670-686 - [c94]Mengting Wan
, Tara Safavi, Sujay Kumar Jauhar, Yujin Kim, Scott Counts, Jennifer Neville, Siddharth Suri, Chirag Shah, Ryen W. White, Longqi Yang, Reid Andersen, Georg Buscher, Dhruv Joshi, Nagu Rangan:
TnT-LLM: Text Mining at Scale with Large Language Models. KDD 2024: 5836-5847 - [c93]Canwen Xu, Corby Rosset, Ethan C. Chau, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Awadallah, Nikhil Rao:
Automatic Pair Construction for Contrastive Post-training. NAACL-HLT (Findings) 2024: 149-162 - [c92]Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang:
MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. WWW (Companion Volume) 2024: 292-301 - [i54]Jiayi Liu, Tinghan Yang, Jennifer Neville:
CliqueParcel: An Approach For Batching LLM Prompts That Jointly Optimizes Efficiency And Faithfulness. CoRR abs/2402.14833 (2024) - [i53]Corby Rosset, Ho-Lam Chung, Guanghui Qin, Ethan C. Chau, Zhuo Feng, Ahmed Awadallah, Jennifer Neville, Nikhil Rao:
Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents. CoRR abs/2402.17896 (2024) - [i52]Mengting Wan, Tara Safavi, Sujay Kumar Jauhar, Yujin Kim, Scott Counts, Jennifer Neville, Siddharth Suri, Chirag Shah, Ryen W. White, Longqi Yang, Reid Andersen, Georg Buscher, Dhruv Joshi, Nagu Rangan:
TnT-LLM: Text Mining at Scale with Large Language Models. CoRR abs/2403.12173 (2024) - [i51]Ying-Chun Lin, Jennifer Neville, Jack W. Stokes, Longqi Yang, Tara Safavi, Mengting Wan, Scott Counts, Siddharth Suri, Reid Andersen, Xiaofeng Xu, Deepak Gupta, Sujay Kumar Jauhar, Xia Song, Georg Buscher, Saurabh Tiwary, Brent J. Hecht, Jaime Teevan:
Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models. CoRR abs/2403.12388 (2024) - [i50]Tobias Schnabel, Jennifer Neville:
Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. CoRR abs/2404.02319 (2024) - [i49]Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen, Mengting Wan, Tara Safavi, Jennifer Neville, Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Sathish Manivannan, Nagu Rangan, Longqi Yang:
The Use of Generative Search Engines for Knowledge Work and Complex Tasks. CoRR abs/2404.04268 (2024) - [i48]Tvrtko Tadic, Cassiano Becker, Jennifer Neville:
Node Similarities under Random Projections: Limits and Pathological Cases. CoRR abs/2404.10148 (2024) - [i47]Zhuoran Lu, Sheshera Mysore, Tara Safavi, Jennifer Neville, Longqi Yang, Mengting Wan:
Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Media. CoRR abs/2405.04656 (2024) - [i46]Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang:
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels. CoRR abs/2405.07526 (2024) - [i45]Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan:
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR abs/2406.01633 (2024) - [i44]Jiaxing Zhang, Jiayi Liu, Dongsheng Luo, Jennifer Neville, Hua Wei:
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation. CoRR abs/2407.15351 (2024) - [i43]Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Kumar Jauhar, Xiaofeng Xu, Xia Song, Jennifer Neville:
WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback. CoRR abs/2408.15549 (2024) - [i42]Ying-Chun Lin, Jennifer Neville:
Improving Node Representation by Boosting Target-Aware Contrastive Loss. CoRR abs/2410.03901 (2024) - [i41]Ying-Chun Lin, Jennifer Neville, Cassiano Becker, Purvanshi Metha, Nabiha Asghar, Vipul Agarwal:
Rethinking Node Representation Interpretation through Relation Coherence. CoRR abs/2411.00653 (2024) - 2023
- [j20]Hogun Park, Jennifer Neville:
Generating post-hoc explanations for Skip-gram-based node embeddings by identifying important nodes with bridgeness. Neural Networks 164: 546-561 (2023) - [c91]Giselle Zeno, Jennifer Neville:
DYANE: DYnamic Attributed Node rolEs Generative Model. CIKM 2023: 3144-3153 - [c90]Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo de Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan:
Hindsight Learning for MDPs with Exogenous Inputs. ICML 2023: 31877-31914 - [c89]Jiayi Liu, Jennifer Neville:
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. KDD 2023: 4527-4538 - [c88]Kiran Tomlinson, Jennifer Neville, Longqi Yang, Mengting Wan, Cao Lu:
Workplace Recommendation with Temporal Network Objectives. KDD 2023: 4958-4969 - [c87]Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li:
Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. WWW 2023: 567-577 - [e3]Brian Williams, Yiling Chen, Jennifer Neville:
Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023. AAAI Press 2023, ISBN 978-1-57735-880-0 [contents] - [i40]Anton Amirov, Chris Quirk, Jennifer Neville:
Creating generalizable downstream graph models with random projections. CoRR abs/2302.08895 (2023) - [i39]Hogun Park, Jennifer Neville:
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness. CoRR abs/2304.12036 (2023) - [i38]Giselle Zeno, Timothy La Fond, Jennifer Neville:
DYMOND: DYnamic MOtif-NoDes Network Generative Model. CoRR abs/2308.00770 (2023) - [i37]Jiayi Liu, Jennifer Neville:
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. CoRR abs/2308.08460 (2023) - [i36]Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, Tara Safavi:
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. CoRR abs/2309.08827 (2023) - [i35]Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Scott Counts, Sarkar Snigdha Sarathi Das, Ali Montazer, Sathish Manivannan, Jennifer Neville, Xiaochuan Ni, Nagu Rangan, Tara Safavi, Siddharth Suri, Mengting Wan, Leijie Wang, Longqi Yang:
Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. CoRR abs/2309.13063 (2023) - [i34]Canwen Xu, Corby Rosset, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Hassan Awadallah, Nikhil Rao:
Contrastive Post-training Large Language Models on Data Curriculum. CoRR abs/2310.02263 (2023) - [i33]Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, Tara Safavi:
PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers. CoRR abs/2311.09180 (2023) - 2022
- [i32]Mengyue Hang, Tobias Schnabel, Longqi Yang, Jennifer Neville:
Lightweight Compositional Embeddings for Incremental Streaming Recommendation. CoRR abs/2202.02427 (2022) - [i31]Susheel Suresh, Danny Godbout, Arko Mukherjee, Mayank Shrivastava, Jennifer Neville, Pan Li:
Federated Graph Representation Learning using Self-Supervision. CoRR abs/2210.15120 (2022) - 2021
- [c86]Mahak Goindani, Jennifer Neville:
Towards Decentralized Social Reinforcement Learning via Ego-Network Extrapolation. AAMAS 2021: 1512-1514 - [c85]Mengyue Hang, Jennifer Neville, Bruno Ribeiro:
A Collective Learning Framework to Boost GNN Expressiveness for Node Classification. ICML 2021: 4040-4050 - [c84]Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma:
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. KDD 2021: 1541-1551 - [c83]Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville:
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. NeurIPS 2021: 15920-15933 - [c82]Giselle Zeno, Timothy La Fond, Jennifer Neville:
DYMOND: DYnamic MOtif-NoDes Network Generative Model. WWW 2021: 718-729 - [i30]Changping Meng, Muhao Chen, Jie Mao, Jennifer Neville:
ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis. CoRR abs/2103.04083 (2021) - [i29]Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville:
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. CoRR abs/2106.05819 (2021) - [i28]Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma:
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. CoRR abs/2106.06586 (2021) - 2020
- [j19]Hoda Eldardiry, Jennifer Neville, Ryan A. Rossi:
Ensemble Learning for Relational Data. J. Mach. Learn. Res. 21: 49:1-49:37 (2020) - [c81]Mahak Goindani, Jennifer Neville:
Cluster-Based Social Reinforcement Learning. AAMAS 2020: 1852-1854 - [c80]Yi-Yu Lai, Jennifer Neville:
MERL: Multi-View Edge Representation Learning in Social Networks. CIKM 2020: 675-684 - [c79]Changping Meng, Muhao Chen, Jie Mao, Jennifer Neville:
ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis. ECIR (1) 2020: 33-49 - [c78]Shikai Fang, Shandian Zhe, Kuang-chih Lee, Kai Zhang, Jennifer Neville:
Online Bayesian Sparse Learning with Spike and Slab Priors. ICDM 2020: 142-151 - [c77]Susheel Suresh, Jennifer Neville:
A Hybrid Model for Learning Embeddings and Logical Rules Simultaneously from Knowledge Graphs. ICDM 2020: 1280-1285 - [c76]Hogun Park, Jennifer Neville:
Role Equivalence Attention for Label Propagation in Graph Neural Networks. PAKDD (2) 2020: 555-567 - [c75]Giselle Zeno, Timothy La Fond, Jennifer Neville:
Dynamic Network Modeling from Motif-Activity. WWW (Companion Volume) 2020: 390-397 - [i27]Mahak Goindani, Jennifer Neville:
Cluster-Based Social Reinforcement Learning. CoRR abs/2003.00627 (2020) - [i26]Mengyue Hang, Jennifer Neville, Bruno Ribeiro:
A Collective Learning Framework to Boost GNN Expressiveness. CoRR abs/2003.12169 (2020) - [i25]Susheel Suresh, Jennifer Neville:
A Hybrid Model for Learning Embeddings and Logical Rules Simultaneously from Knowledge Graphs. CoRR abs/2009.10800 (2020)
2010 – 2019
- 2019
- [j18]Zenglin Xu, Bin Liu, Shandian Zhe, Haoli Bai, Zihan Wang, Jennifer Neville:
Variational Random Function Model for Network Modeling. IEEE Trans. Neural Networks Learn. Syst. 30(1): 318-324 (2019) - [c74]Yi-Yu Lai, Jennifer Neville, Dan Goldwasser:
TransConv: Relationship Embedding in Social Networks. AAAI 2019: 4130-4138 - [c73]Jiasen Yang, Vinayak A. Rao, Jennifer Neville:
A Stein-Papangelou Goodness-of-Fit Test for Point Processes. AISTATS 2019: 226-235 - [c72]Hogun Park, Jennifer Neville:
Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks. IJCAI 2019: 3223-3230 - [c71]Changping Meng, Jiasen Yang, Bruno Ribeiro, Jennifer Neville:
HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings. KDD 2019: 783-792 - [c70]Mahak Goindani, Jennifer Neville:
Social Reinforcement Learning to Combat Fake News Spread. UAI 2019: 1006-1016 - [i24]Guilherme Gomes, Vinayak A. Rao, Jennifer Neville:
Community detection over a heterogeneous population of non-aligned networks. CoRR abs/1904.05332 (2019) - [i23]S. Chandra Mouli, Leonardo Teixeira, Jennifer Neville, Bruno Ribeiro:
Deep Lifetime Clustering. CoRR abs/1910.00547 (2019) - 2018
- [j17]Sebastián Moreno, Joseph J. Pfeiffer III, Jennifer Neville:
Scalable and exact sampling method for probabilistic generative graph models. Data Min. Knowl. Discov. 32(6): 1561-1596 (2018) - [j16]Sebastián Moreno, Jennifer Neville, Sergey Kirshner:
Tied Kronecker Product Graph Models to Capture Variance in Network Populations. ACM Trans. Knowl. Discov. Data 12(3): 35:1-35:40 (2018) - [j15]Timothy La Fond, Jennifer Neville, Brian Gallagher:
Designing Size Consistent Statistics for Accurate Anomaly Detection in Dynamic Networks. ACM Trans. Knowl. Discov. Data 12(4): 46:1-46:49 (2018) - [c69]Changping Meng, S. Chandra Mouli, Bruno Ribeiro, Jennifer Neville:
Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction. AAAI 2018: 3778-3787 - [c68]Xi Tan, Vinayak A. Rao, Jennifer Neville:
Nested CRP with Hawkes-Gaussian Processes. AISTATS 2018: 1289-1298 - [c67]Guilherme Gomes, Vinayak A. Rao, Jennifer Neville:
Multi-level Hypothesis Testing for Populations of Heterogeneous Networks. ICDM 2018: 977-982 - [c66]Jiasen Yang, Qiang Liu, Vinayak A. Rao, Jennifer Neville:
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy. ICML 2018: 5557-5566 - [c65]Mengyue Hang, Ian Pytlarz, Jennifer Neville:
Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction. KDD 2018: 321-330 - [c64]Foster J. Provost, James Hodson, Jeannette M. Wing, Qiang Yang, Jennifer Neville:
Societal Impact of Data Science and Artificial Intelligence. KDD 2018: 2872-2873 - [c63]Xi Tan, Vinayak A. Rao, Jennifer Neville:
The Indian Buffet Hawkes Process to Model Evolving Latent Influences. UAI 2018: 795-804 - [i22]Guilherme Gomes, Vinayak A. Rao, Jennifer Neville:
Multi-level hypothesis testing for populations of heterogeneous networks. CoRR abs/1809.02512 (2018) - [i21]Mengyue Hang, Ian Pytlarz, Jennifer Neville:
Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction. CoRR abs/1811.06912 (2018) - [i20]Oleg Kiselyov, Tiark Rompf, Jennifer Neville, Yukiyoshi Kameyama:
Meta-Programming for Statistical Machine Learning (NII Shonan Meeting 2018-7). NII Shonan Meet. Rep. 2018 (2018) - 2017
- [j14]Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield, Theodore L. Willke:
Graphlet decomposition: framework, algorithms, and applications. Knowl. Inf. Syst. 50(3): 689-722 (2017) - [c62]John Moore, Jennifer Neville:
Deep Collective Inference. AAAI 2017: 2364-2372 - [c61]Jennifer Neville:
How to Exploit Relationships to Improve Predictions. ICTIR 2017: 167 - [c60]Jiasen Yang, Bruno Ribeiro, Jennifer Neville:
Should We Be Confident in Peer Effects Estimated From Social Network Crawls? ICWSM 2017: 708-711 - [c59]Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville:
Unified Representation and Lifted Sampling for Generative Models of Social Networks. IJCAI 2017: 3798-3806 - [c58]Jiasen Yang, Vinayak A. Rao, Jennifer Neville:
Decoupling Homophily and Reciprocity with Latent Space Network Models. UAI 2017 - [i19]S. Chandra Mouli, Abhishek Naik, Bruno Ribeiro, Jennifer Neville:
Identifying User Survival Types via Clustering of Censored Social Network Data. CoRR abs/1703.03401 (2017) - [i18]Jiasen Yang, Bruno Ribeiro, Jennifer Neville:
Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls. CoRR abs/1707.07716 (2017) - 2016
- [c57]Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville:
Sampling of Attributed Networks from Hierarchical Generative Models. KDD 2016: 1155-1164 - [c56]Yi-Yu Lai, Chang Li, Dan Goldwasser, Jennifer Neville:
Better Together: Combining Language and Social Interactions into a Shared Representation. TextGraphs@NAACL-HLT 2016: 29-33 - [e2]Paul N. Bennett, Vanja Josifovski, Jennifer Neville, Filip Radlinski:
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016. ACM 2016, ISBN 978-1-4503-3716-8 [contents] - [i17]Iman Al-Odah, Jennifer Neville:
Combining Gradient Boosting Machines with Collective Inference to Predict Continuous Values. CoRR abs/1607.00110 (2016) - [i16]Timothy La Fond, Jennifer Neville, Brian Gallagher:
Size-Consistent Statistics for Anomaly Detection in Dynamic Networks. CoRR abs/1608.00712 (2016) - 2015
- [c55]Stephen Mussmann, John Moore, Joseph John Pfeiffer III, Jennifer Neville:
Incorporating Assortativity and Degree Dependence into Scalable Network Models. AAAI 2015: 238-246 - [c54]Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield:
Efficient Graphlet Counting for Large Networks. ICDM 2015: 1-10 - [c53]Ransen Niu, Sebastián Moreno, Jennifer Neville:
Analyzing the Transferability of Collective Inference Models Across Networks. ICDM Workshops 2015: 908-916 - [c52]Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett:
Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks. WWW 2015: 853-863 - [i15]Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield:
Fast Parallel Graphlet Counting for Large Networks. CoRR abs/1506.04322 (2015) - [i14]Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville:
Using Bayesian Network Representations for Effective Sampling from Generative Network Models. CoRR abs/1507.03168 (2015) - 2014
- [j13]Georgios B. Giannakis, Francis R. Bach, Raphael Cendrillon, Michael W. Mahoney, Jennifer Neville:
Signal Processing for Big Data [From the Guest Editors]. IEEE Signal Process. Mag. 31(5): 15-16 (2014) - [c51]Joseph John Pfeiffer III, Jennifer Neville, Paul N. Bennett:
Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference. CIKM 2014: 639-648 - [c50]Sebastián Moreno, Joseph J. Pfeiffer III, Jennifer Neville, Sergey Kirshner:
A Scalable Method for Exact Sampling from Kronecker Family Models. ICDM 2014: 440-449 - [c49]Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett:
Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning. ICDM 2014: 490-499 - [c48]Stephen Mussmann, John Moore, Joseph J. Pfeiffer III, Jennifer Neville:
Assortativity in Chung Lu Random Graph Models. SNAKDD 2014: 3:1-3:8 - [c47]Nesreen K. Ahmed, Nick G. Duffield, Jennifer Neville, Ramana Rao Kompella:
Graph sample and hold: a framework for big-graph analytics. KDD 2014: 1446-1455 - [c46]Joseph J. Pfeiffer III, Sebastián Moreno, Timothy La Fond, Jennifer Neville, Brian Gallagher:
Attributed graph models: modeling network structure with correlated attributes. WWW 2014: 831-842 - [i13]Nesreen K. Ahmed, Christopher Cole, Jennifer Neville:
Learning the Latent State Space of Time-Varying Graphs. CoRR abs/1403.3707 (2014) - [i12]Nesreen K. Ahmed, Nick G. Duffield, Jennifer Neville, Ramana Rao Kompella:
Graph Sample and Hold: A Framework for Big-Graph Analytics. CoRR abs/1403.3909 (2014) - [i11]Timothy La Fond, Jennifer Neville, Brian Gallagher:
Anomaly Detection in Dynamic Networks of Varying Size. CoRR abs/1411.3749 (2014) - 2013
- [j12]Gabriel Ghinita, Jennifer Neville, Shawn D. Newsam:
LBSN 2012 workshop report: the Fifth ACM SIGSPATIAL International Workshop on Location-Based Social Networks (Redondo Beach, California - November 6, 2012). ACM SIGSPATIAL Special 5(1): 13-14 (2013) - [j11]Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella:
Network Sampling: From Static to Streaming Graphs. ACM Trans. Knowl. Discov. Data 8(2): 7:1-7:56 (2013) - [c45]Sebastián Moreno, Jennifer Neville:
Network Hypothesis Testing Using Mixed Kronecker Product Graph Models. ICDM 2013: 1163-1168 - [c44]Sebastián Moreno, Jennifer Neville, Sergey Kirshner:
Learning mixed kronecker product graph models with simulated method of moments. KDD 2013: 1052-1060 - [c43]Rongjing Xiang, Jennifer Neville:
Collective inference for network data with copula latent markov networks. WSDM 2013: 647-656 - [c42]Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson:
Modeling dynamic behavior in large evolving graphs. WSDM 2013: 667-676 - 2012
- [j10]Ryan A. Rossi, Luke K. McDowell, David William Aha, Jennifer Neville:
Transforming Graph Data for Statistical Relational Learning. J. Artif. Intell. Res. 45: 363-441 (2012) - [j9]Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad, Tao Wang:
Correcting evaluation bias of relational classifiers with network cross validation. Knowl. Inf. Syst. 30(1): 31-55 (2012) - [c41]Hoda Eldardiry, Jennifer Neville:
An analysis of how ensembles of collective classifiers improve predictions in graphs. CIKM 2012: 225-234 - [c40]Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella:
Network Sampling Designs for Relational Classification. ICWSM 2012 - [c39]Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella:
Space-efficient sampling from social activity streams. BigMine 2012: 53-60 - [c38]Karthik Nagaraj, Charles Edwin Killian, Jennifer Neville:
Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems. NSDI 2012: 353-366 - [c37]Ryan A. Rossi, Jennifer Neville:
Time-Evolving Relational Classification and Ensemble Methods. PAKDD (1) 2012: 1-13 - [c36]Joseph J. Pfeiffer III, Timothy La Fond, Sebastián Moreno, Jennifer Neville:
Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures. SocialCom/PASSAT 2012: 154-165 - [c35]Timothy La Fond, Dan Roberts, Jennifer Neville, James Tyler, Stacey L. Connaughton:
The Impact of Communication Structure and Interpersonal Dependencies on Distributed Teams. SocialCom/PASSAT 2012: 558-565 - [c34]Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson:
Role-dynamics: fast mining of large dynamic networks. WWW (Companion Volume) 2012: 997-1006 - [e1]Gabriel Ghinita, Jennifer Neville, Shawn D. Newsam:
Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2012, Redondo Beach, California, USA, November 6, 2012. ACM 2012, ISBN 978-1-4503-1698-9 [contents] - [i10]Joseph J. Pfeiffer III, Timothy La Fond, Sebastián Moreno, Jennifer Neville:
Fast Generation of Large Scale Social Networks with Clustering. CoRR abs/1202.4805 (2012) - [i9]Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson:
Role-Dynamics: Fast Mining of Large Dynamic Networks. CoRR abs/1203.2200 (2012) - [i8]Ryan A. Rossi, Luke K. McDowell, David W. Aha, Jennifer Neville:
Transforming Graph Representations for Statistical Relational Learning. CoRR abs/1204.0033 (2012) - [i7]Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson:
Dynamic Behavioral Mixed-Membership Model for Large Evolving Networks. CoRR abs/1205.2056 (2012) - [i6]Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella:
Space-Efficient Sampling from Social Activity Streams. CoRR abs/1206.4952 (2012) - [i5]Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella:
Network Sampling: From Static to Streaming Graphs. CoRR abs/1211.3412 (2012) - 2011
- [j8]Douglas Baumann, Susanne E. Hambrusch, Jennifer Neville:
Gender demographics trends and changes in U.S. CS departments. Commun. ACM 54(11): 38-42 (2011) - [j7]Ravish Khosla, Sonia Fahmy, Y. Charlie Hu, Jennifer Neville:
Prediction models for long-term Internet prefix availability. Comput. Networks 55(3): 873-889 (2011) - [j6]S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel:
Introduction to the special issue on mining and learning with graphs. Mach. Learn. 82(2): 91-93 (2011) - [j5]Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville, Mourad Ouzzani, Ihab F. Ilyas:
Guided data repair. Proc. VLDB Endow. 4(5): 279-289 (2011) - [c33]Hoda Eldardiry, Jennifer Neville:
Across-Model Collective Ensemble Classification. AAAI 2011: 343-349 - [c32]Rongjing Xiang, Jennifer Neville:
Understanding Propagation Error and Its Effect on Collective Classification. ICDM 2011: 834-843 - [c31]Ankit Kuwadekar, Jennifer Neville:
Relational Active Learning for Joint Collective Classification Models. ICML 2011: 385-392 - [c30]Joseph J. Pfeiffer III, Jennifer Neville:
Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. ICWSM 2011 - [c29]Tao Wang, Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad:
Correcting Bias in Statistical Tests for Network Classifier Evaluation. ECML/PKDD (3) 2011: 506-521 - [c28]Rongjing Xiang, Jennifer Neville:
Relational Learning with One Network: An Asymptotic Analysis. AISTATS 2011: 779-788 - [i4]Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville, Mourad Ouzzani, Ihab F. Ilyas:
Guided Data Repair. CoRR abs/1103.3103 (2011) - [i3]Joseph J. Pfeiffer III, Jennifer Neville:
Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. CoRR abs/1104.0319 (2011) - [i2]Ryan A. Rossi, Jennifer Neville:
Representations and Ensemble Methods for Dynamic Relational Classification. CoRR abs/1111.5312 (2011) - 2010
- [c27]Sebastián Moreno, Sergey Kirshner, Jennifer Neville, S. V. N. Vishwanathan:
Tied Kronecker product graph models to capture variance in network populations. Allerton 2010: 1137-1144 - [c26]Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville:
Ranking for data repairs. ICDE Workshops 2010: 23-28 - [c25]Ravish Khosla, Sonia Fahmy, Y. Charlie Hu, Jennifer Neville:
Predicting Prefix Availability in the Internet. INFOCOM 2010: 216-220 - [c24]Ryan A. Rossi, Jennifer Neville:
Modeling the evolution of discussion topics and communication to improve relational classification. SOMA@KDD 2010: 89-97 - [c23]Nesreen K. Ahmed, Fredrick J. Berchmans, Jennifer Neville, Ramana Rao Kompella:
Time-based sampling of social network activity graphs. MLG@KDD 2010: 1-9 - [c22]Hoda Eldardiry, Jennifer Neville:
Multi-network fusion for collective inference. MLG@KDD 2010: 46-54 - [c21]Chris Mayfield, Jennifer Neville, Sunil Prabhakar:
ERACER: a database approach for statistical inference and data cleaning. SIGMOD Conference 2010: 75-86 - [c20]Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville, Mourad Ouzzani:
GDR: a system for guided data repair. SIGMOD Conference 2010: 1223-1226 - [c19]Timothy La Fond, Jennifer Neville:
Randomization tests for distinguishing social influence and homophily effects. WWW 2010: 601-610 - [c18]Rongjing Xiang, Jennifer Neville, Monica Rogati:
Modeling relationship strength in online social networks. WWW 2010: 981-990
2000 – 2009
- 2009
- [c17]Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad:
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data. ICDM 2009: 397-406 - [c16]Indika Kahanda, Jennifer Neville:
Using Transactional Information to Predict Link Strength in Online Social Networks. ICWSM 2009 - 2008
- [j4]James A. Hendler, Philipp Cimiano, Dmitri A. Dolgov, Anat Levin, Peter Mika, Brian Milch, Louis-Philippe Morency, Boris Motik, Jennifer Neville, Erik B. Sudderth, Luis von Ahn:
AI's 10 to Watch. IEEE Intell. Syst. 23(3): 9-19 (2008) - [j3]Jennifer Neville, David D. Jensen:
A bias/variance decomposition for models using collective inference. Mach. Learn. 73(1): 87-106 (2008) - [c15]Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch, Jennifer Neville, Reynold Cheng:
Database Support for Probabilistic Attributes and Tuples. ICDE 2008: 1053-1061 - [c14]Umang Sharan, Jennifer Neville:
Temporal-Relational Classifiers for Prediction in Evolving Domains. ICDM 2008: 540-549 - [c13]Pelin Angin, Jennifer Neville:
A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation. ICDM 2008: 707-712 - [c12]Rongjing Xiang, Jennifer Neville:
Pseudolikelihood EM for Within-network Relational Learning. ICDM 2008: 1103-1108 - 2007
- [j2]Jennifer Neville, David D. Jensen:
Relational Dependency Networks. J. Mach. Learn. Res. 8: 653-692 (2007) - [c11]Jennifer Neville, David D. Jensen:
Bias/Variance Analysis for Relational Domains. ILP 2007: 27-28 - 2005
- [c10]Jennifer Neville:
Structure Learning for Statistical Relational Models. AAAI 2005: 1656-1657 - [c9]Jennifer Neville, David D. Jensen:
Leveraging Relational Autocorrelation with Latent Group Models. ICDM 2005: 322-329 - [c8]Jennifer Neville, Özgür Simsek, David D. Jensen, John Komoroske, Kelly Palmer, Henry G. Goldberg:
Using relational knowledge discovery to prevent securities fraud. KDD 2005: 449-458 - [i1]Jennifer Neville, David D. Jensen:
Leveraging relational autocorrelation with latent group models. Probabilistic, Logical and Relational Learning 2005 - 2004
- [c7]Jennifer Neville, David D. Jensen:
Dependency Networks for Relational Data. ICDM 2004: 170-177 - [c6]David D. Jensen, Jennifer Neville, Brian Gallagher:
Why collective inference improves relational classification. KDD 2004: 593-598 - 2003
- [j1]Amy McGovern, Lisa Friedland, Michael Hay, Brian Gallagher, Andrew S. Fast, Jennifer Neville, David D. Jensen:
Exploiting relational structure to understand publication patterns in high-energy physics. SIGKDD Explor. 5(2): 165-172 (2003) - [c5]Jennifer Neville, David D. Jensen, Brian Gallagher:
Simple Estimators for Relational Bayesian Classifiers. ICDM 2003: 609-612 - [c4]David D. Jensen, Jennifer Neville, Michael Hay:
Avoiding Bias when Aggregating Relational Data with Degree Disparity. ICML 2003: 274-281 - [c3]Jennifer Neville, David D. Jensen, Lisa Friedland, Michael Hay:
Learning relational probability trees. KDD 2003: 625-630 - 2002
- [c2]David D. Jensen, Jennifer Neville:
Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. ICML 2002: 259-266 - [c1]David D. Jensen, Jennifer Neville:
Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. ILP 2002: 101-116
Coauthor Index
Joseph J. Pfeiffer III
aka: Joseph John Pfeiffer III
aka: Joseph John Pfeiffer III
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