Publications | LINQS

2024

Charles Dickens, Connor Pryor, Changyu Gao, Alon Albalak, Eriq Augustine, William Wang, Stephen Wright, and Lise Getoor. A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic Systems. arXiv. 2024.

Charles Dickens. A Unifying Mathematical Framework for Neural-Symbolic Systems. University of California, Santa Cruz. 2024.

Charles Dickens, Changyu Gao, Connor Pryor, Stephen Wright, and Lise Getoor. Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning. International Conference on Machine Learning (ICML). 2024.

Charles Dickens, Connor Pryor, and Lise Getoor. Modeling Patterns for Neural-Symbolic Reasoning using Energy-Based Models. AAAI Spring Symposium on Empowering Machine Learning and Large Language Models with Domain and Commonsense Knowledge. 2024.

2023

Eriq Augustine. Building Practical Statistical Relational Learning Systems. University of California, Santa Cruz. 2023.

Yi-Lin Tuan, Alon Albalak, Wenda Xu, Michael S. Saxon, Connor Pryor, Lise Getoor, and William Yang Wang. CausalDialogue: Modeling Utterance-level Causality in Conversations. Annual Meeting of the Association for Computational Linguistics (ACL). 2023.

Eriq Augustine and Lise Getoor. Collective Grounding: Applying Database Techniques to Grounding Templated Models. International Conference on Very Large Data Bases (VLDB). 2023.

Connor Pryor, Charles Dickens, and Lise Getoor. Deep Neuro-Symbolic Weight Learning in Neural Probabilistic Soft Logic. Knowledge and Logical Reasoning in the Era of Data-Driven Learning (KLR). 2023.

Kaiwen Zhou, Kaizhi Zheng, Connor Pryor, Yilin Shen, Hongxia Jin, Lise Getoor, and Xin Eric Wang. ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation. International Conference on Machine Learning (ICML). 2023.

Connor Pryor*, Charles Dickens*, Eriq Augustine, Alon Albalak, William Yang Wang, and Lise Getoor. NeuPSL: Neural Probabilistic Soft Logic. International Joint Conference on Artificial Intelligence (IJCAI). 2023.

Charles Dickens, Alex Miller, and Lise Getoor. Online Collective Demand Forecasting for Bike Sharing Services. Hawaii International Conference on System Sciences. 2023.

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Alex Miller, Eriq Augustine, Elijah Pandolfo, and Lise Getoor. PSL-GWAS: A Microbial GWAS Method Using Statistical Relational Learning. University of California, Santa Cruz. 2023.

Connor Pryor, Quan Yuan, Jeremiah Zhe Liu, Seyed Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, and Lise Getoor. Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. Annual Meeting of the Association for Computational Linguistics (ACL). 2023.

2022

Djellel Difallah, Diego Saez-Trumper, Eriq Augustine, Robert West, and Leila Zia. Crosslingual Section Title Alignment in Wikipedia. IEEE International Conference on Big Data (BigData). 2022.

Charles Dickens, Connor Pryor, Eriq Augustine, Alon Albalak, and Lise Getoor. Efficient Learning Losses for Deep Hinge-Loss Markov Random Fields. Workshop on Tractable Probabilistic Modeling (TPM). 2022.

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Eriq Augustine, Pegah Jandaghi, Alon Albalak, Connor Pryor, Charles Dickens, William Wang, and Lise Getoor. Emotion Recognition in Conversation using Probabilistic Soft Logic. arXiv. 2022.

Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi, Connor Pryor, Luke Yoffe, Deepak Ramachandran, Lise Getoor, Jay Pujara, and William Yang Wang. FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue. Conference on Empirical Methods in Natural Language Processing (EMNLP). 2022.

Varun Embar, Sriram Srinivasan, and Lise Getoor. Learning Explainable Templated Graphical Models. Conference on Uncertainty in Artificial Intelligence (UAI). 2022.

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Hossam Sharara and Lise Getoor. Multi-relational Affinity Propagation. International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2022.

Eriq Augustine, Connor Pryor, Charles Dickens, Jay Pujara, William Yang Wang, and Lise Getoor. Visual Sudoku Puzzle Classification: A Suite of Collective Neuro-Symbolic Tasks. International Workshop on Neural-Symbolic Learning and Reasoning (NeSy). 2022.

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2021

Varun Embar, Sriram Srinivasan, and Lise Getoor. A Comparison of Statistical Relational Learning and Graph Neural Networks for Aggregate Graph Queries. Machine Learning. 2021.

Sriram Srinivasan, Charles Dickens, Eriq Augustine, Golnoosh Farnadi, and Lise Getoor. A Taxonomy of Weight Learning Methods for Statistical Relational Learning. Machine Learning. 2021.

Charles Dickens*, Connor Pryor*, Eriq Augustine, Alex Miller, and Lise Getoor. Context-Aware Online Collective Inference for Templated Graphical Models. International Conference on Machine Learning (ICML). 2021.

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Varun Embar, Andrey Kan, Bunyamin Sisman, Christos Faloutsos, and Lise Getoor. DiffXtract: Joint Discriminative Product Attribute-Value Extraction. IEEE International Conference on Big Knowledge (ICBK). 2021.

Yi-Lin Tuan, Connor Pryor, Wenhu Chen, Lise Getoor, and William Yang Wang. Local Explanation of Dialogue Response Generation. Conference on Neural Information Processing Systems (NeurIPS). 2021.

Charles Dickens*, Eriq Augustine*, Connor Pryor, and Lise Getoor. Negative Weights in Hinge-Loss Markov Random Fields. Workshop on Tractable Probabilistic Modeling (TPM). 2021.

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Stefano Balietti, Lise Getoor, Daniel G. Goldstein, and Duncan J. Watts. Reducing Opinion Polarization: Effects of Exposure to Similar People with Differing Political Views. Proceedings of the National Academy of Sciences (PNAS). 2021.

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Stefano Balietti, Lise Getoor, Daniel G. Goldstein, and Duncan Watts. Talking about Politics: How Informal Communication Shapes Views about Redistribution. International Conference on Computational Social Science (IC2S2). 2021.

2020

Shawn Bailey, Yue Zhang, Arti Ramesh, Jennifer Golbeck, and Lise Getoor. A Structured and Linguistic Approach to Understanding Recovery and Relapse in AA. ACM Transactions on the Web (TWEB). 2020.

Sriram Srinivasan, Golnoosh Farnadi, and Lise Getoor. BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic. AAAI Conference on Artificial Intelligence (AAAI). 2020.

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Babak Salami, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, and Dan Suciu. Causal Relational Learning. International Conference on Management of Data (SIGMOD). 2020.

Alex Miller, Naum Markenzon, Varun Embar, and Lise Getoor. Collective Bio-Entity Recognition in Scientific Documents using Hinge-Loss Markov Random Fields. International Workshop on Mining and Learning with Graphs (MLG). 2020.

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Varun Embar, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Christos Faloutsos, and Lise Getoor. Contrastive Entity Linkage: Mining Variational Attributes From Large Catalogs for Entity Linkage. Automated Knowledge Base Construction (AKBC). 2020.

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Yatong Chen, Byran Tor, Eriq Augustine, and Lise Getoor. Decoupled Smoothing in Probabilistic Soft Logic. International Workshop on Mining and Learning with Graphs (MLG). 2020.

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Varun Embar, Sriram Srinivasan, and Lise Getoor. Estimating Aggregate Properties in Relational Networks with Unobserved Data. International Workshop on Statistical Relational AI (StarAI). 2020.

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Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, and Lise Getoor. Generating and Understanding Personalized Explanations in Hybrid Recommender Systems. ACM Transactions on Interactive Intelligent Systems (TIIS). 2020.

Charles Dickens, Rishika Singh, and Lise Getoor. HyperFair: A Soft Approach to Integrating Fairness Criteria. RecSys Workshop on Responsible Recommendation (FAccTRec). 2020.

Rajdipa Chowdhury, Sriram Srinivasan, and Lise Getoor. Joint Estimation of User And Publisher Credibility for Fake News Detection. International Conference on Information and Knowledge Management (CIKM). 2020.

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Sriram Srinivasan, Eriq Augustine, and Lise Getoor. Tandem Inference: An Out-of-Core Streaming Algorithm for Very Large-Scale Relational Inference. AAAI Conference on Artificial Intelligence (AAAI). 2020.

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Sriram Srinivasan. Towards Fast and Accurate Structured Prediction. University of California, Santa Cruz. 2020.

Aaron Rodden, Tarun Salh, Eriq Augustine, and Lise Getoor. VMI-PSL: Visual Model Inspector for Probabilistic Soft Logic. ACM Conference on Recommender Systems (RecSys). 2020.

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2019

Angelika Kimmig, Alex Memory, Renée J. Miller, and Lise Getoor. A Collective, Probabilistic Approach to Schema Mapping Using Diverse Noisy Evidence. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2019.

Golnoosh Farnadi, Behrouz Babaki, and Lise Getoor. A Declarative Approach to Fairness in Relational Domains. IEEE Data Engineering Bulletin. 2019.

Varun Embar, Jay Pujara, and Lise Getoor. Collective Alignment of Large-Scale Ontologies. AKBC Workshop on Federated Knowledge Bases. 2019.

Pigi Kouki, Jay Pujara, Christopher Marcum, Laura Koehly, and Lise Getoor. Collective Entity Resolution in Multi-Relational Familial Networks. International Journal on Knowledge and Information Systems (KAIS). 2019.

Dhanya Sridhar and Lise Getoor. Estimating Causal Effects of Tone in Online Debates. International Joint Conference on Artificial Intelligence (IJCAI). 2019.

Sriram Srinivasan, Nikhil S Rao, Karthik Subbaian, and Lise Getoor. Identifying Facet Mismatches in Search Via Micrographs. International Conference on Information and Knowledge Management (CIKM). 2019.

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Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor. Interpretable Engagement Models for MOOCs Using Hinge-Loss Markov Random Fields. IEEE Transactions on Learning Technologies (TLT). 2019.

Sriram Srinivasan, Behrouz Babaki, Golnoosh Farnadi, and Lise Getoor. Lifted Hinge-Loss Markov Random Fields. AAAI Conference on Artificial Intelligence (AAAI). 2019.

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Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, and Lise Getoor. Personalized Explanations for Hybrid Recommender Systems. Intelligent User Interfaces (IUI). 2019.

Varun Embar, Sriram Srinivasan, and Lise Getoor. Tractable Marginal Inference for Hinge-Loss Markov Random Fields. Workshop on Tractable Probabilistic Modeling (TPM). 2019.

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Eriq Augustine, Theodoros Rekatsinas, and Lise Getoor. Tractable Probabilistic Reasoning Through Effective Grounding. Workshop on Tractable Probabilistic Modeling (TPM). 2019.

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Sabina Tomkins and Lise Getoor. Understanding Hybrid-MOOC Effectiveness with a Collective Socio-Behavioral Model. Journal of Educational Data Mining (JEDM). 2019.

2018

Eriq Augustine and Lise Getoor. A Comparison of Bottom-Up Approaches to Grounding for Templated Markov Random Fields. Conference on Machine Learning and Systems (MLSys). 2018.

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Golnoosh Farnadi, Pigi Kouki, Spencer K. Thompson, Sriram Srinivasan, and Lise Getoor. A Fairness-Aware Hybrid Recommender System. RecSys Workshop on Responsible Recommendation (FAccTRec). 2018.

Sabina Tomkins, Lise Getoor, Yunfei Chen, and Yi Zhang. A Socio-Linguistic Model for Cyberbullying Detection. International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2018.

Yue Zhang, Arti Ramesh, Jennifer Golbeck, Dhanya Sridhar, and Lise Getoor. A Structured Approach to Understanding Recovery and Relapse in AA. The Web Conference (WWW). 2018.

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Varun Embar, Golnoosh Farnadi, Jay Pujara, and Lise Getoor. Aligning Product Categories Using Anchor Products. WSDM Workshop on Workshop on Knowledge Base Construction, Reasoning and Mining (KBCOM). 2018.

Johnnie Chang, Robert Chen, Jay Pujara, and Lise Getoor. Clustering System Data Using Aggregate Measures. Conference on Machine Learning and Systems (MLSys). 2018.

Jonathan W. Berry, Kina Kincher-Winoto, Cynthia A. Phillips, Eriq Augustine, and Lise Getoor. Entity Resolution at Large Scale: Benchmarking and Algorithmics. Sandia National Lab. 2018.

Dhanya Sridhar, Aaron Springer, Victoria Hollis, Steve Whittaker, and Lise Getoor. Estimating Causal Effects of Exercise From Mood Logging Data. ICML Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (CausalML). 2018.

Golnoosh Farnadi, Behrouz Babaki, and Lise Getoor. Fairness in Relational Domains. AAAI/ACM Conference on AI, Ethics, and Society (AIES). 2018.

Golnoosh Farnadi, Behrouz Babaki, and Lise Getoor. Fairness-Aware Relational Learning and Inference. AAAI Workshop on Declarative Learning Based Programming (DeLBP). 2018.

Eriq Augustine and Golnoosh Farnadi. MLtrain: Collective Reasoning with Probabilistic Soft Logic. Conference on Uncertainty in Artificial Intelligence (UAI). 2018.

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Pigi Kouki. Resolution, Recommendation, and Explanation in Richly Structured Social Networks. University of California, Santa Cruz. 2018.

Dhanya Sridhar, Jay Pujara, and Lise Getoor. Scalable Probabilistic Causal Structure Discovery. International Joint Conference on Artificial Intelligence (IJCAI). 2018.

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Varun Embar, Dhanya Sridhar, Golnoosh Farnadi, and Lise Getoor. Scalable Structure Learning for Probabilistic Soft Logic. International Workshop on Statistical Relational AI (StarAI). 2018.

Sabina Tomkins, Steve Isley, Ben London, and Lise Getoor. Sustainability at Scale: Bridging the Intention-Behavior Gap with Sustainable Recommendations. ACM Conference on Recommender Systems (RecSys). 2018.

Sabina Tomkins, Golnoosh Farnadi, Brian Amantullah, Lise Getoor, and Steven Minton. The Impact of Environmental Stressors on Human Trafficking. ICWSM Workshop on Beyond Online Data. 2018.

Sabina Tomkins, Golnoosh Farnadi, Brian Amantullah, Lise Getoor, and Steven Minton. The Impact of Environmental Stressors on Human Trafficking. IEEE International Conference on Data Mining (ICDM). 2018.

Arti Ramesh and Lise Getoor. Topic Evolution Models for Long-running MOOCs. International Conference on Web Information Systems Engineering (WISE). 2018.

2017

Angelika Kimmig, Alex Memory, Renée J. Miller, and Lise Getoor. A Collective, Probabilistic Approach to Schema Mapping. IEEE International Conference on Data Engineering (ICDE). 2017.

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Pigi Kouki, Jay Pujara, Christopher Marcum, Laura Koehly, and Lise Getoor. Collective Entity Resolution in Familial Networks. IEEE International Conference on Data Mining (ICDM). 2017.

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Sabina Tomkins, Lise Getoor, Yunfei Chen, and Yi Zhang. Detecting Cyber-Bullying From Sparse Data and Inconsistent Labels. Learning from Limited Labeled Data Workshop (LLD). 2017.

Sabina Tomkins, Jay Pujara, and Lise Getoor. Disambiguating Energy Disaggregation: A Collective Probabilistic Approach. International Joint Conference on Artificial Intelligence (IJCAI). 2017.

Stephen Bach, Matthias Broecheler, Bert Huang, and Lise Getoor. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. Journal of Machine Learning Research (JMLR). 2017.

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Arti Ramesh, Mario Rodriguez, and Lise Getoor. Multi-Relational Influence Models for Online Professional Networks. International Conference on Web Intelligence (WI). 2017.

Sungchul Kim, Nikhil Kini, Jay Pujara, Eunyee Koh, and Lise Getoor. Probabilistic Visitor Stitching on Cross-Device Web Logs. The Web Conference (WWW). 2017.

Golnoosh Farnadi, Stephen Bach, Marie-Francine Moens, Lise Getoor, and Martine De Cock. Soft Quantification in Statistical Relational Learning. Machine Learning. 2017.

Jay Pujara, Eriq Augustine, and Lise Getoor. Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short. Conference on Empirical Methods in Natural Language Processing (EMNLP). 2017.

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Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, and Lise Getoor. User Preferences for Hybrid Explanations. ACM Conference on Recommender Systems (RecSys). 2017.

Dhanya Sridhar, Jay Pujara, and Lise Getoor. Using Noisy Extractions to Discover Causal Knowledge. NIPS Workshop on Automated Knowledge Base Construction (AKBC). 2017.

2016

Dhanya Sridhar, Shobeir Fakhraei, and Lise Getoor. A Probabilistic Approach for Collective Similarity-Based Drug-Drug Interaction Prediction. Bioinformatics. 2016.

Arti Ramesh. A Probabilistic Approach to Modeling Socio-Behavioral Interactions. University of Maryland, College Park. 2016.

Shobeir Fakhraei, Sridhar Dhanya, Jay Pujara, and Lise Getoor. Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. International Conference on Knowledge Discovery and Data Mining (KDD). 2016.

Sathappan Muthiah, Bert Huang, Jaime Arredondo, David Mares, Lise Getoor, Graham Katz, and Naren Ramakrishnan. Capturing Planned Protests From Open Source Indicators. AI Magazine. 2016.

Pigi Kouki, Christopher Marcum, Laura Koehly, and Lise Getoor. Entity Resolution in Familial Networks. International Workshop on Mining and Learning with Graphs (MLG). 2016.

Jay Pujara and Lise Getoor. Generic Statistical Relational Entity Resolution in Knowledge Graphs. International Workshop on Statistical Relational AI (StarAI). 2016.

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Dhanya Sridhar and Lise Getoor. Joint Probabilistic Inference of Causal Structure. KDD Workshop on Causal Discovery. 2016.

Sabina Tomkins, Arti Ramesh, and Lise Getoor. Predicting Post-Test Performance From Online Student Behavior: A High School MOOC Case Study. Educational Data Mining (EDM). 2016.

Dhanya Sridhar and Lise Getoor. Probabilistic Inference for Causal Structure Discovery. UAI Workshop on Causation. 2016.

Jay Pujara. Probabilistic Models for Scalable Knowledge Graph Construction. University of Maryland, College Park. 2016.

Theodoros Rekatsinas, Amol Deshpande, Luna Dong, Lise Getoor, and Divesh Srivastava. SourceSight: Enabling Effective Source Selection. International Conference on Management of Data (SIGMOD). 2016.

Ben London, Bert Huang, and Lise Getoor. Stability and Generalization in Structured Prediction. Journal of Machine Learning Research (JMLR). 2016.

Shachi Kumar, Jay Pujara, Lise Getoor, David Mares, Dipak Gupta, and Ellen Riloff. Unsupervised Models for Predicting Strategic Relations between Organizations. International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2016.

2015

Jay Pujara, Ben London, and Lise Getoor. Budgeted Online Collective Inference. Conference on Uncertainty in Artificial Intelligence (UAI). 2015.

Galileo Mark Namata, Ben London, and Lise Getoor. Collective Graph Identification. ACM Transactions on Knowledge Discovery from Data (TKDD). 2015.

Shobeir Fakhraei, James Foulds, Madhusudana Shashanka, and Lise Getoor. Collective Spammer Detection in Evolving Multi-Relational Social Networks. International Conference on Knowledge Discovery and Data Mining (KDD). 2015.

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Shobeir Fakhraei, Eberechukwu Onukwugha, and Lise Getoor. Data Analytics for Pharmaceutical Discoveries. Healthcare Data Analytics. 2015.

Theodoros Rekatsinas, Xin Luna Dong, Lise Getoor, and Divesh Srivastava. Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration. Conference on Innovative Data Systems Research (CIDR). 2015.

Theodoros Rekatsinas, Saurav Ghosh, Sumiko Mekaru, Elaine Nsoesie, John Brownstein, Lise Getoor, and Naren Ramakrishnan. Forecasting Rare Disease Outbreaks Using Multiple Data Sources. Statistical Analysis and Data Mining. 2015.

Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, and Yan Liu. HawkesTopic: A Joint Model for Network Inference and Topic Modeling From Text-Based Cascades. International Conference on Machine Learning (ICML). 2015.

Stephen Bach. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic: A Scalable Approach to Structured Prediction. University of Maryland, College Park. 2015.

Pigi Kouki, Shobeir Fakhraei, James Foulds, Magdalini Eirinaki, and Lise Getoor. HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems. ACM Conference on Recommender Systems (RecSys). 2015.

Dhanya Sridhar, James Foulds, Marilyn Walker, Bert Huang, and Lise Getoor. Joint Models of Disagreement and Stance in Online Debate. Annual Meeting of the Association for Computational Linguistics (ACL). 2015.

James Foulds, Shachi Kumar, and Lise Getoor. Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models. International Conference on Machine Learning (ICML). 2015.

Angelika Kimmig, Lilyana Mihalkova, and Lise Getoor. Lifted Graphical Models: A Survey. Machine Learning. 2015.

Ben London. On the Stability of Structured Prediction. University of Maryland, College Park. 2015.

Jay Pujara, Ben London, Lise Getoor, and William Cohen. Online Inference for Knowledge Graph Construction.. International Workshop on Statistical Relational AI (StarAI). 2015.

Stephen Bach*, Bert Huang*, Jordan Boyd-Graber, and Lise Getoor. Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. International Conference on Machine Learning (ICML). 2015.

Theodoros Rekatsinas. Quality-Aware Data Source Management. University of Maryland, College Park. 2015.

Adam Grycner, Gerhard Weikum, Jay Pujara, James Foulds, and Lise Getoor. RELLY: Inferring Hypernym Relationships between Relational Phrases. Conference on Empirical Methods in Natural Language Processing (EMNLP). 2015.

Theodoros Rekatsinas, Saurav Ghosh, Sumiko Mekaru, Elaine Nsoesie, John Brownstein, Lise Getoor, and Naren Ramakrishnan. SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources. SIAM International Conference on Data Mining (SDM). 2015.

Golnoosh Farnadi, Stephen Bach, Marjon Blondeel, Marie-Francine Moens, Lise Getoor, and Martine De Cock. Statistical Relational Learning with Soft Quantifiers. International Conference on Inductive Logic Programming (ILP). 2015.

Ben London, Bert Huang, and Lise Getoor. The Benefits of Learning with Strongly Convex Approximate Inference. International Conference on Machine Learning (ICML). 2015.

Arti Ramesh, Mario Rodriguez, and Lise Getoor. Understanding Influence in Online Professional Networks. NIPS Workshop on Networks in Social and Information Sciences. 2015.

Stephen Bach, Bert Huang, and Lise Getoor. Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees. International Conference on Artificial Intelligence and Statistics (AISTATS). 2015.

Jay Pujara, Hui Miao, Lise Getoor, and William Cohen. Using Semantics & Statistics to Turn Data Into Knowledge. AI Magazine. 2015.

Arti Ramesh, Shachi Kumar, James Foulds, and Lise Getoor. Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums. Annual Meeting of the Association for Computational Linguistics (ACL). 2015.

2014

Naren Ramakrishnan, Patrick Butler, Nathan Self, Rupinder Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Christopher Kuhlman, Achla Marathe, Liang Zhao, Hua Ting, Bert Huang, Aravind Srinivasan, Khoa Trinh, Lise Getoor, Graham Katz, Andy Doyle, Chris Ackermann, Ilya Zavorin, Jim Ford, Kristin Summers, Youssef Fayed, Jaime Arredondo, Dipak Gupta, and David Mares. 'Beating the News' with EMBERS: Forecasting Civil Unrest Using Open Source Indicators. International Conference on Knowledge Discovery and Data Mining (KDD). 2014.

Adam Grycner, Gerhard Weikum, Jay Pujara, James Foulds, and Lise Getoor. A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases. Conference on Neural Information Processing Systems (NeurIPS). 2014.

Jay Pujara and Lise Getoor. Building Dynamic Knowledge Graphs. NIPS Workshop on Automated Knowledge Base Construction (AKBC). 2014.

Ben London and Lise Getoor. Collective Classification of Network Data. Data Classification: Algorithms and Applications. 2014.

Dhanya Sridhar, James Foulds, Bert Huang, Marilyn Walker, and Lise Getoor. Collective Classification of Stance and Disagreement in Online Debate Forums. Bay Area Machine Learning Symposium (BayLearn). 2014.

Dhanya Sridhar, Lise Getoor, and Marilyn Walker. Collective Stance Classification of Posts in Online Debate Forums. ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media. 2014.

Golnoosh Farnadi, Stephen Bach, Marie-Francine Moens, Lise Getoor, and Martine De Cock. Extending PSL with Fuzzy Quantifiers. International Workshop on Statistical Relational AI (StarAI). 2014.

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor. Learning Latent Engagement Patterns of Students in Online Courses. AAAI Conference on Artificial Intelligence (AAAI). 2014.

Shobeir Fakhraei, Bert Huang, Louiqa Raschid, and Lise Getoor. Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 2014.

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Ben London, Bert Huang, and Lise Getoor. On the Strong Convexity of Variational Inference. NIPS Workshop on Advances in Variational Inference (AVI). 2014.

Ben London, Bert Huang, Benjamin Taskar, and Lise Getoor. PAC-Bayesian Collective Stability. International Conference on Artificial Intelligence and Statistics (AISTATS). 2014.

Stephen Bach, Bert Huang, and Lise Getoor. Probabilistic Soft Logic for Social Good. KDD Workshop on Data Science for Social Good. 2014.

Stephen Bach, Bert Huang, and Lise Getoor. Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies. NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML). 2014.

Walaa Eldin Moustafa, Angelika Kimmig, Amol Deshpande, and Lise Getoor. Subgraph Pattern Matching Over Uncertain Graphs with Identity Linkage Uncertainty. IEEE International Conference on Data Engineering (ICDE). 2014.

Bradley Skaggs and Lise Getoor. Topic Modeling for Wikipedia Link Disambiguation. ACM Transactions on Information Systems (TOIS). 2014.

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor. Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs. ACM Conference on Learning at Scale (L@S). 2014.

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor. Understanding MOOC Discussion Forums Using Seeded LDA. ACL Workshop on Innovative Use of NLP for Building Educational Applications (BEA). 2014.

2013

Bert Huang, Angelika Kimmig, Lise Getoor, and Jennifer Golbeck. A Flexible Framework for Probabilistic Models of Social Trust. International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP). 2013.

Hui Miao, Xiangyang Liu, Bert Huang, and Lise Getoor. A Hypergraph-Partitioned Vertex Programming Approach for Large-Scale Consensus Optimization. IEEE International Conference on Big Data (BigData). 2013.

Ben London, Sameh Khamis, Stephen Bach, Bert Huang, Lise Getoor, and Larry Davis. Collective Activity Detection Using Hinge-Loss Markov Random Fields. CVPR Workshop on Structured Prediction: Tractability, Learning and Inference. 2013.

Shobeir Fakhraei, Bert Huang, and Lise Getoor. Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction. NIPS Workshop on Machine Learning in Computational Biology. 2013.

Ben London, Bert Huang, Benjamin Taskar, and Lise Getoor. Collective Stability in Structured Prediction: Generalization From One Example. International Conference on Machine Learning (ICML). 2013.

Shobeir Fakhraei, Louiqa Raschid, and Lise Getoor. Drug-Target Interaction Prediction for Drug Repurposing with Probabilistic Similarity Logic. KDD Workshop on Data Mining in Bioinformatics (BIOKDD). 2013.

Bert Huang, Ben London, Benjamin Taskar, and Lise Getoor. Empirical Analysis of Collective Stability. ICML Workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs (SLG). 2013.

Lise Getoor and Ashwin Machanavajjhala. Entity Resolution in Big Data. International Conference on Knowledge Discovery and Data Mining (KDD). 2013.

Walaa Eldin Moustafa, Hui Miao, Amol Deshpande, and Lise Getoor. GrDB: A System for Declarative and Interactive Analysis of Noisy Information Networks. International Conference on Management of Data (SIGMOD). 2013.

Ben London, Bert Huang, and Lise Getoor. Graph-Based Generalization Bounds for Learning Binary Relations. arXiv. 2013.

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Stephen Bach, Bert Huang, Ben London, and Lise Getoor. Hinge-Loss Markov Random Fields: Convex Inference for Structured Prediction. Conference on Uncertainty in Artificial Intelligence (UAI). 2013.

Jay Pujara, Hui Miao, and Lise Getoor. Joint Judgments with a Budget: Strategies for Reducing the Cost of Inference. ICML Workshop on Learning with Test-Time Budgets. 2013.

Jay Pujara, Hui Miao, Lise Getoor, and William Cohen. Knowledge Graph Identification. International Semantic Web Conference (ISWC). 2013.

Jeonhyung Kang, Kristina Lerman, and Lise Getoor. LA-LDA: A Limited Attention Topic Model for Social Recommendation. International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP). 2013.

Jay Pujara, Hui Miao, Lise Getoor, and William Cohen. Large-Scale Knowledge Graph Identification Using PSL. AAAI Workshop on Semantics for Big Data. 2013.

Jay Pujara, Hui Miao, Lise Getoor, and William Cohen. Large-Scale Knowledge Graph Identification Using PSL. ICML Workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs (SLG). 2013.

Stephen Bach, Bert Huang, and Lise Getoor. Large-margin Structured Learning for Link Ranking. NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications. 2013.

Stephen Bach, Bert Huang, and Lise Getoor. Learning Latent Groups with Hinge-Loss Markov Random Fields. ICML Workshop on Inferning Interactions between Inference and Learning (Inferning). 2013.

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor. Modeling Learner Engagement in MOOCs Using Probabilistic Soft Logic. NIPS Workshop on Data Driven Education. 2013.

Ben London, Theodoros Rekatsinas, Bert Huang, and Lise Getoor. Multi-Relational Learning Using Weighted Tensor Decomposition with Modular Loss. arXiv. 2013.

Bibtex paper link

Jay Pujara, Hui Miao, Lise Getoor, and William Cohen. Ontology-Aware Partitioning for Knowledge Graph Identification. CIKM Workshop on Automated Knowledge Base Construction (AKBC). 2013.

Ben London, Bert Huang, Benjamin Taskar, and Lise Getoor. PAC-Bayes Generalization Bounds for Randomized Structured Prediction. NIPS Workshop on Perturbation, Optimization, and Statistics. 2013.

Mohammad Rastegari, Jonghyun Choi, Shobeir Fakhraei, Hal Daume III, and Larry Davis. Predictable Dual-View Hashing. International Conference on Machine Learning (ICML). 2013.

2012

Angelika Kimmig, Stephen Bach, Matthias Broecheler, Bert Huang, and Lise Getoor. A Short Introduction to Probabilistic Soft Logic. NIPS Workshop on Probabilistic Programming: Foundations and Applications. 2012.

Walaa Eldin Moustafa, Amol Deshpande, and Lise Getoor. Ego-Centric Graph Pattern Census. IEEE International Conference on Data Engineering (ICDE). 2012.

Lise Getoor and Ashwin Machanavajjhala. Entity Resolution for Social Network Analysis and Mining. International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2012.

Lise Getoor and Ashwin Machanavajjhala. Entity Resolution: Theory, Practice & Open Challenges. International Conference on Very Large Data Bases (VLDB). 2012.

Bibtex paper slides

Lise Getoor and Ashwin Machanavajjhala. Entity Resolution: Theory, Practice, and Open Challenges. AAAI Conference on Artificial Intelligence (AAAI). 2012.

Hossam Sharara, Lisa Singh, and Lise Getoor. Finding Prominent Actors in Dynamic Affiliation Networks. Human Journal. 2012.

Alex Memory, Angelika Kimmig, Stephen Bach, Louiqa Raschid, and Lise Getoor. Graph Summarization in Annotated Data Using Probabilistic Soft Logic. ICSW Workshop on Uncertainty Reasoning for the Semantic Web (URSW). 2012.

Galileo Mark Namata. Identifying Graphs From Noisy Observational Data. University of Maryland, College Park. 2012.

Ben London, Bert Huang, and Lise Getoor. Improved Generalization Bounds for Large-Scale Structured Prediction. NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks. 2012.

Jay Pujara and Peter Skomoroch. Large-Scale Hierarchical Topic Models. NIPS Workshop on Big Learning: Algorithms, Systems, and Tools. 2012.

Theodoros Rekatsinas, Amol Deshpande, and Lise Getoor. Local Structure and Determinism in Probabilistic Databases. International Conference on Management of Data (SIGMOD). 2012.

Ben London, Theodoros Rekatsinas, Bert Huang, and Lise Getoor. Multi-Relational Weighted Tensor Decomposition. NIPS Workshop on Spectral Learning. 2012.

Heasoo Hwang, Hady Lauw, Lise Getoor, and Alexandros Ntoulas. Organizing User Search Histories. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2012.

Elena Zheleva, Evimaria Terzi, and Lise Getoor. Privacy in Social Networks. Synthesis Lectures on Data Mining and Knowledge Discovery. 2012.

Bert Huang, Angelika Kimmig, Lise Getoor, and Jennifer Golbeck. Probabilistic Soft Logic for Trust Analysis in Social Networks. International Workshop on Statistical Relational AI (StarAI). 2012.

Galileo Mark Namata, Ben London, Lise Getoor, and Bert Huang. Query-Driven Active Surveying for Collective Classification. International Workshop on Mining and Learning with Graphs (MLG). 2012.

Stephen Bach, Matthias Broecheler, Lise Getoor, and Dianne O'Leary. Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization. Conference on Neural Information Processing Systems (NeurIPS). 2012.

Bert Huang, Stephen Bach, Eric Norris, Jay Pujara, and Lise Getoor. Social Group Modeling with Probabilistic Soft Logic. NIPS Workshop on Social Network and Social Media Analysis: Methods, Models and Applications. 2012.

Hossam Sharara, Lisa Singh, Lise Getoor, and Janet Mann. Stability vs. Diversity: Understanding the Dynamics of Actors in Time-Varying Affiliation Networks. International Conference on Social Informatics. 2012.

Papadimitriou Panagiotis, Tsaparas Panayiotis, Fuxman Ariel, and Lise Getoor. TACI: Taxonomy-Aware Catalog Integration. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2012.

Arti Ramesh, Jaebong Yoo, Shitian Shen, Lise Getoor, and Jihie Kim. User Role Prediction in Online Discussion Forums Using Probabilistic Soft Logic. NIPS Workshop on Personalizing Education With Machine Learning. 2012.

2011

Louis Licamele and Lise Getoor. A Method for the Detection of Meaningful and Reproducible Group Signatures From Gene Expression Profiles.. Journal of Bioinformatics and Computational Biology (JBCB). 2011.

Anon Plangprasopchok, Kristina Lerman, and Lise Getoor. A Probabilistic Approach for Learning Folksonomies From Structured Data. International Conference on Web Search and Data Mining (WSDM). 2011.

Daozheng Chen, Mustafa Bilgic, Lise Getoor, David Jacobs, Lilyana Mihalkova, and Tom Yeh. Active Inference for Retrieval in Camera Networks. IEEE Workshop on Person-Oriented Vision. 2011.

Hossam Sharara, Lise Getoor, and Myra Norton. Active Surveying: A Probabilistic Approach for Identifying Key Opinion Leaders. International Joint Conference on Artificial Intelligence (IJCAI). 2011.

Galileo Mark Namata, Stanley Kok, and Lise Getoor. Collective Graph Identification. International Conference on Knowledge Discovery and Data Mining (KDD). 2011.

Bibtex paper supplementary material

Walaa Eldin Moustafa, Galileo Mark Namata, Amol Deshpande, and Lise Getoor. Declarative Analysis of Noisy Information Networks. ICDE Workshop on Graph Data Management (GDM). 2011.

Hossam Sharara, William Rand, and Lise Getoor. Differential Adaptive Diffusion: Understanding Diversity and Learning Whom to Trust in Viral Marketing. International Conference on Web and Social Media (ICWSM). 2011.

Daozheng Chen, Mustafa Bilgic, Lise Getoor, and David Jacobs. Dynamic Processing Allocation in Video. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2011.

Lise Getoor and Lilyana Mihalkova. Exploiting Statistical and Relational Information on the Web and in Social Media. International Conference on Web Search and Data Mining (WSDM). 2011.

Hossam Sharara, Awalin Sopan, Galileo Mark Namata, Lise Getoor, and Lisa Singh. G-PARE: A Visual Analytic Tool for Comparative Analysis of Uncertain Graphs. IEEE Conference on Visual Analytics Science and Technology (VAST). 2011.

Steven Minton, Matthew Michelson, Kane See, Sofus Macskassy, Bora C. Gazen, and Lise Getoor. Improving Classifier Performance by Autonomously Collecting Background Knowledge From the Web. International Conference on Machine Learning and Applications (ICMLA). 2011.

Lilyana Mihalkova, Walaa Eldin Moustafa, and Lise Getoor. Learning to Predict Web Collaborations. WSDM Workshop on User Modeling for Web Applications (UMWA). 2011.

Hossam Sharara, Daniel Halgin, Lise Getoor, and Steve Borgatti. Multi-Dimensional Trajectory Analysis for Career Histories. International Sunbelt Social Network Conference. 2011.

Elena Zheleva. Prediction, Evolution and Privacy in Social and Affiliation Networks. University of Maryland, College Park. 2011.

Elena Zheleva and Lise Getoor. Privacy in Social Networks: A Survey. Social Network Data Analytics. 2011.

Jay Pujara, Ben London, and Lise Getoor. Reducing Label Cost by Combining Feature Labels and Crowdsourcing. ICML Workshop on Combining Learning Strategies to Reduce Label Cost. 2011.

Hossam Sharara, Lisa Singh, Lise Getoor, and Janet Mann. Understanding Actor Loyalty to Event-Based Groups in Affiliation Networks. Social Network Analysis and Mining (SNAM). 2011.

Jay Pujara, Hal Daume III, and Lise Getoor. Using Classifier Cascades for Scalable E-Mail Classification. International Conference on Email and Anti-Spam (CEAS). 2011.

Mustafa Bilgic and Lise Getoor. Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition. Journal of Artificial Intelligence Research (JAIR). 2011.

2010

Galileo Mark Namata, Hossam Sharara, and Lise Getoor. A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks. Link Mining: Models, Algorithms, and Applications. 2010.

Mustafa Bilgic and Lise Getoor. Active Inference for Collective Classification. AAAI Conference on Artificial Intelligence (AAAI). 2010.

Mustafa Bilgic, Lilyana Mihalkova, and Lise Getoor. Active Learning for Networked Data. International Conference on Machine Learning (ICML). 2010.

Hossam Sharara, Lise Getoor, and Myra Norton. Active Surveying. NIPS Workshop on Networks Across Disciplines: Theory and Applications. 2010.

Hossam Sharara, Myra Norton, and Lise Getoor. Active Surveying for Leadership Identification. International Sunbelt Social Network Conference. 2010.

Jay Pujara and Lise Getoor. Coarse-to-Fine, Cost-Sensitive Classification of E-Mail. NIPS Workshop on Coarse-to-Fine Processing. 2010.

Prithviraj Sen, Galileo Mark Namata, Mustafa Bilgic, and Lise Getoor. Collective Classification. Encyclopedia of Machine Learning. 2010.

Matthias Broecheler and Lise Getoor. Computing Marginal Distributions Over Continuous Markov Networks for Statistical Relational Learning. Conference on Neural Information Processing Systems (NeurIPS). 2010.

Stephen Bach, Matthias Broecheler, Stanley Kok, and Lise Getoor. Decision-Driven Models with Probabilistic Soft Logic. NIPS Workshop on Predictive Models in Personalized Medicine. 2010.

Indrajit Bhattacharya and Lise Getoor. Entity Resolution. Encyclopedia of Machine Learning. 2010.

Hossam Sharara and Lise Getoor. Group Detection. Encyclopedia of Machine Learning. 2010.

Anon Plangprasopchok, Kristina Lerman, and Lise Getoor. Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata. International Conference on Knowledge Discovery and Data Mining (KDD). 2010.

Elena Zheleva, Lise Getoor, and Sunita Sarawagi. Higher-Order Graphical Models for Classification in Social and Affiliation Networks. NIPS Workshop on Networks Across Disciplines: Theory and Applications. 2010.

Louis Licamele and Lise Getoor. Indirect Two-Sided Relative Ranking: A Robust Similarity Measure for Gene Expression Data. BMC Bioinformatics. 2010.

Mustafa Bilgic. Information Acquisition in Structured Domains. University of Maryland, College Park. 2010.

Janardhan Doppa, Jun Yu, Prasad Tadepalli, and Lise Getoor. Learning Algorithms for Link Prediction Based on Chance Constraints. European Conference on Machine Learning (ECML). 2010.

Lise Getoor. Link Mining and Link Discovery. Encyclopedia of Machine Learning. 2010.

Galileo Mark Namata and Lise Getoor. Link Prediction. Encyclopedia of Machine Learning. 2010.

Matthias Broecheler, Lilyana Mihalkova, and Lise Getoor. Probabilistic Similarity Logic. Conference on Uncertainty in Artificial Intelligence (UAI). 2010.

Prithviraj Sen, Amol Deshpande, and Lise Getoor. Read-Once Functions and Query Evaluation in Probabilistic Databases. International Conference on Very Large Data Bases (VLDB). 2010.

Elena Zheleva, John Guiver, Eduarda Mendes Rodrigues, and Natasa Milic-Frayling. Statistical Models of Music-Listening Sessions in Social Media. The Web Conference (WWW). 2010.

2009

Galileo Mark Namata and Lise Getoor. A Pipeline Approach to Graph Identification. International Workshop on Mining and Learning with Graphs (MLG). 2009.

Prithviraj Sen, Amol Deshpande, and Lise Getoor. Bisimulation-Based Approximate Lifted Inference. Conference on Uncertainty in Artificial Intelligence (UAI). 2009.

Janardhan Doppa, Jun Yu, Prasad Tadepalli, and Lise Getoor. Chance-Constrained Programs for Link Prediction. NIPS Workshop on Analyzing Networks and Learning with Graphs. 2009.

Elena Zheleva, Hossam Sharara, and Lise Getoor. Co-Evolution of Social and Affiliation Networks. International Conference on Knowledge Discovery and Data Mining (KDD). 2009.

Galileo Mark Namata, Prithviraj Sen, Mustafa Bilgic, and Lise Getoor. Collective Classification for Text Classification. Text Mining: Classification, Clustering, and Applications. 2009.

Mihales Polymeropoulos, Louis Licamele, Simona Volpi, Kendra Mack, Shruti Mitkus, Eugene Carstea, Lise Getoor, and Christian Lavedan. Common Effect of Antipsychotics on the Biosynthesis and Regulation of Fatty Acids and Cholesterol Supports a Key Role of Lipid Homeostasis in Schizophrenia. Schizophrenia Research. 2009.

Vladimir Barash, Marc Smith, Lise Getoor, and Howard Welser. Distinguishing Knowledge Vs Social Capital in Social Media with Roles and Context. International Conference on Web and Social Media (ICWSM). 2009.

Daozheng Chen, Mustafa Bilgic, Lise Getoor, and David Jacobs. Efficient Resource-Constrained Retrospective Analysis of Long Video Sequences. NIPS Workshop on Adaptive Sensing, Active Learning and Experimental Design: Theory, Methods and Applications. 2009.

Hassan Sayyadi and Lise Getoor. Future Rank: Ranking Scientific Articles by Predicting Their Future PageRank. SIAM International Conference on Data Mining (SDM). 2009.

Amol Deshpande, Lise Getoor, and Prithviraj Sen. Graphical Models for Uncertain Data. Managing and Mining Uncertain Data. 2009.

Galileo Mark Namata and Lise Getoor. Identifying Graphs From Noisy and Incomplete Data. KDD Workshop on Knowledge Discovery from Uncertain Data. 2009.

Karl Schnaitter, Neoklis Polyzotis, and Lise Getoor. Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications. International Conference on Very Large Data Bases (VLDB). 2009.

Mustafa Bilgic and Lise Getoor. Link-Based Active Learning. NIPS Workshop on Analyzing Networks and Learning with Graphs. 2009.

Barna Saha and Lise Getoor. On Maximum Coverage in the Streaming Model & Application to Multi-Topic Blog-Watch. SIAM International Conference on Data Mining (SDM). 2009.

Swapna Somasundaran, Galileo Mark Namata, Lise Getoor, and Janyce Wiebe. Opinion Graphs for Polarity and Discourse Classification. ACL Workshop on Graph-based Methods for Natural Language Processing (TextGraphs). 2009.

Prithviraj Sen, Amol Deshpande, and Lise Getoor. PrDB: Managing and Exploiting Rich Correlations in Probabilistic Databases. The VLDB Journal. 2009.

Matthias Broecheler and Lise Getoor. Probabilistic Similarity Logic. International Workshop on Statistical Relational Learning (SRL). 2009.

Mustafa Bilgic and Lise Getoor. Reflect and Correct: A Misclassification Prediction Approach to Active Inference. ACM Transactions on Knowledge Discovery from Data (TKDD). 2009.

Prithviraj Sen. Representing and Querying Uncertain Data. University of Maryland, College Park. 2009.

Swapna Somasundaran, Galileo Mark Namata, Janyce Wiebe, and Lise Getoor. Supervised and Unsupervised Methods in Employing Discourse Relations for Improving Opinion Polarity Classification. Conference on Empirical Methods in Natural Language Processing (EMNLP). 2009.

Hossam Sharara, Lisa Singh, Lise Getoor, and Janet Mann. The Dynamics of Actor Loyalty to Groups in Affiliation Networks. International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2009.

Elena Zheleva and Lise Getoor. To Join or Not to Join: The Illusion of Privacy in Social Networks with Mixed Public and Private User Profiles. The Web Conference (WWW). 2009.

2008

Rezarta Islamaj, Lise Getoor, and John Wilbur. A Feature Generation Algorithm with Applications to Biological Sequence Classification. Computational Methods of Feature Selection. 2008.

Prithviraj Sen, Galileo Mark Namata, Mustafa Bilgic, Lise Getoor, Brian Gallagher, and Tina Eliassi-Rad. Collective Classification in Network Data. AI Magazine. 2008.

Indrajit Bhattacharya and Lise Getoor. Collective Relational Clustering. Constrained Clustering: Advances in Algorithms, Theory, and Applications. 2008.

Prithviraj Sen and Lise Getoor. Cost-Sensitive Learning with Conditional Markov Networks. Data Mining and Knowledge Discovery. 2008.

Mustafa Bilgic and Lise Getoor. Effective Label Acquisition for Collective Classification. International Conference on Knowledge Discovery and Data Mining (KDD). 2008.

Prithviraj Sen, Amol Deshpande, and Lise Getoor. Exploiting Shared Correlations in Probabilistic Databases. International Conference on Very Large Data Bases (VLDB). 2008.

Barna Saha and Lise Getoor. Group Proximity Measure for Recommending Groups in Online Social Networks. KDD Workshop on Social Network Mining and Analysis. 2008.

Hyunmo Kang, Lise Getoor, Ben Shneiderman, Mustafa Bilgic, and Louis Licamele. Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation. IEEE Transactions on Visualization and Computer Graphics (TVCG). 2008.

Marc Smith, Vladimir Barash, Lise Getoor, and Hady Lauw. Leveraging Social Context for Searching Social Media. CIKM Workshop on Search in Social Media (SSM). 2008.

Tamer Elsayed, Doug Oard, Galileo Mark Namata, and Lise Getoor. Personal Name Resolution in Email: A Heuristic Approach. University of Maryland, College Park. 2008.

Tamer Elsayed, Doug Oard, and Galileo Mark Namata. Resolving Personal Names in Email Using Context Expansion. Annual Meeting of the Association for Computational Linguistics (ACL). 2008.

Thomas Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, and Prasad Tadepalli. Structured Machine Learning: The Next Ten Years. Machine Learning. 2008.

Elena Zheleva, Alek Kolcz, and Lise Getoor. Trusting Spam Reporters: A Reporter-Based Reputation System for Email Filtering. ACM Transactions on Information Systems (TOIS). 2008.

Elena Zheleva, Lise Getoor, Jennifer Golbeck, and Ugur Kuter. Using Friendship Ties and Family Circles for Link Prediction. KDD Workshop on Social Network Mining and Analysis. 2008.

2007

Galileo Mark Namata, Brian Staats, Lise Getoor, and Ben Shneiderman. A Dual-View Approach to Interactive Network Visualization. International Conference on Information and Knowledge Management (CIKM). 2007.

Hamid Haidarian-Shahri, Galileo Mark Namata, Saket Navlakha, Amol Deshpande, and Nick Roussopoulos. A Graph-Based Approach to Vehicle Tracking in Traffic Camera Video Streams. International Workshop on Data Management for Sensor Networks (DMSN). 2007.

Hyunmo Kang, Lise Getoor, and Lisa Singh. C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership. IEEE Conference on Visual Analytics Science and Technology (VAST). 2007.

Rezarta Islamaj, Lise Getoor, and W. John Wilbur. Characterizing RNA Secondary-Structure Features and Their Effects on Splice-Site Prediction. ICDM Workshop on Mining and Management of Biological Data. 2007.

Indrajit Bhattacharya and Lise Getoor. Collective Entity Resolution in Relational Data. ACM Transactions on Knowledge Discovery from Data (TKDD). 2007.

Mustafa Bilgic, Galileo Mark Namata, and Lise Getoor. Combining Collective Classification and Link Prediction. ICDM Workshop on Mining Graphs and Complex Structures. 2007.

Octavian Udrea and Lise Getoor. Combining Statistical and Logical Inference for Ontology Alignment. IJCAI Workshop on Semantic Web for Collaborative Knowledge Acquisition (SWeCKa). 2007.

Rezarta Islamaj, Lise Getoor, W. John Wilbur, and Stephen Mount. Features Generated for Computational Splice-Site Prediction Correspond to Functional Elements. BMC Bioinformatics. 2007.

Bibtex paper link

Hyunmo Kang, Vivek Sehgal, and Lise Getoor. GeoDDupe: A Novel Interface for Interactive Entity Resolution in Geospatial Data. International Conference Information Visualization (IV). 2007.

Daphne Koller, Nir Friedman, Lise Getoor, and Benjamin Taskar. Graphical Models in a Nutshell. An Introduction to Statistical Relational Learning. 2007.

Octavian Udrea, Lise Getoor, and Renée J. Miller. HOMER: Ontology Alignment Visualization and Analysis. Asian Semantic Web Conference (ASWC). 2007.

Octavian Udrea, Renée J. Miller, and Lise Getoor. HOMER: Ontology Visualization and Analysis. International Semantic Web Conference (ISWC). 2007.

Lisa Singh and Lise Getoor. Increasing the Predictive Power of Affiliation Networks.. IEEE Data Engineering Bulletin. 2007.

Lise Getoor and Benjamin Taskar. Introduction to Statistical Relational Learning. Introduction to Statistical Relational Learning. 2007.

Octavian Udrea, Lise Getoor, and Renée J. Miller. Leveraging Data and Structure in Ontology Integration. International Conference on Management of Data (SIGMOD). 2007.

Prithviraj Sen and Lise Getoor. Link-Based Classification. University of Maryland, College Park. 2007.

Indrajit Bhattacharya and Lise Getoor. Online Collective Entity Resolution. AAAI Conference on Artificial Intelligence (AAAI). 2007.

Elena Zheleva and Lise Getoor. Preserving the Privacy of Sensitive Relationships in Graph Data. KDD Workshop on Privacy, Security, and Trust in KDD (PinKDD). 2007.

Edward Hung, Lise Getoor, and V. S. Subrahmanian. Probabilistic Interval XML. ACM Transactions on Computational Logic (TOCL). 2007.

Lise Getoor, Nir Friedman, Daphne Koller, Avi Pfeffer, and Benjamin Taskar. Probabilistic Relational Models. An Introduction to Statistical Relational Learning. 2007.

Indrajit Bhattacharya and Lise Getoor. Query-Time Entity Resolution. Journal of Artificial Intelligence Research (JAIR). 2007.

Christopher Diehl, Galileo Mark Namata, and Lise Getoor. Relationship Identification for Social Network Discovery. AAAI Conference on Artificial Intelligence (AAAI). 2007.

Prithviraj Sen, Amol Deshpande, and Lise Getoor. Representing Tuple and Attribute Uncertainty in Probabilistic Databases. ICDM Workshop on Data Mining on Uncertain Data. 2007.

Prithviraj Sen and Amol Deshpande. Representing and Querying Correlated Tuples in Probabilistic Databases. IEEE International Conference on Data Engineering (ICDE). 2007.

Rezarta Islamaj, Lise Getoor, W. John Wilbur, and Stephen Mount. SplicePort - An Interactive Splice-Site Analysis Tool. Nucleic Acids Research. 2007.

Mustafa Bilgic and Lise Getoor. VOILA: Efficient Feature-Value Acquisition for Classification. AAAI Conference on Artificial Intelligence (AAAI). 2007.

Hyunmo Kang, Lise Getoor, and Lisa Singh. Visual Analysis of Dynamic Group Membership in Temporal Social Networks. SIGKDD Explorations. 2007.

Lisa Singh, Mitchell Beard, Lise Getoor, and M. Brian Blake. Visual Mining of Multi-Modal Social Networks at Different Abstraction Levels. International Conference Information Visualization (IV). 2007.

2006

Rezarta Islamaj, Lise Getoor, and W. John Wilbur. A Feature Generation Algorithm for Sequences with Application to Splice Site Prediction. Workshop on Feature Selection for Data Mining (FSDM). 2006.

Indrajit Bhattacharya and Lise Getoor. A Latent Dirichlet Model for Unsupervised Entity Resolution. SIAM International Conference on Data Mining (SDM). 2006.

Lise Getoor. An Introduction to Probabilistic Graphical Models for Relational Data. IEEE Data Engineering Bulletin. 2006.

Indrajit Bhattacharya and Lise Getoor. Collective Entity Resolution in Relational Data. IEEE Data Engineering Bulletin. 2006.

Indrajit Bhattacharya. Collective Entity Resolution in Relational Data. University of Maryland, College Park. 2006.

Prithviraj Sen and Lise Getoor. Cost-Sensitive Learning with Conditional Markov Networks. International Conference on Machine Learning (ICML). 2006.

Prithviraj Sen and Lise Getoor. Cost-Sensitive Learning with Conditional Markov Networks. SDM Workshop on Link Analysis, Counterterrorism and Security. 2006.

Mustafa Bilgic, Louis Licamele, Lise Getoor, and Ben Shneiderman. D-Dupe: An Interactive Tool for Entity Resolution in Social Networks. IEEE Conference on Visual Analytics Science and Technology (VAST). 2006.

Prithviraj Sen and Lise Getoor. Empirical Comparison of Approximate Inference Algorithms for Networked Data. International Workshop on Statistical Relational Learning (SRL). 2006.

Vivek Sehgal, Lise Getoor, and Peter Viechnicki. Entity Resolution in Geospatial Data Integration. International Symposium on Geographic Information Systems (GIS). 2006.

Indrajit Bhattacharya and Lise Getoor. Entity Resolution in Social Networks. International Sunbelt Social Network Conference. 2006.

Indrajit Bhattacharya and Lise Getoor. Entity Resolutions in Graphs. Mining Graph Data. 2006.

Bin Zhao, Prithviraj Sen, and Lise Getoor. Event Classification and Relationship Labeling in Affiliation Networks. ICML Workshop on Statistical Network Analysis. 2006.

Rezarta Islamaj, Lise Getoor, and W. John Wilbur. Feature Generation Algorithm: An Application to Splice Site Prediction. European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD). 2006.

Galileo Mark Namata, Lise Getoor, and Christopher Diehl. Inferring Organizational Titles in Online Communications. ICML Workshop on Statistical Network Analysis. 2006.

Gregory Piatetsky-Shapiro, Robert Grossman, Chabane Djeraba, Ronen Feldman, Lise Getoor, and Mohammed Zaki. Is There a Grand Challenge or X-Prize for Data Mining?. International Conference on Knowledge Discovery and Data Mining (KDD). 2006.

Christopher Diehl, Lise Getoor, and Galileo Mark Namata. Name Reference Resolution in Organizational Email Archives. SIAM International Conference on Data Mining (SDM). 2006.

Lise Getoor and John Grant. PRL: A Logical Approach to Probabilistic Relational Models. Machine Learning. 2006.

Louis Licamele and Lise Getoor. Predicting Protein-Protein Interactions Using Relational Features. ICML Workshop on Statistical Network Analysis. 2006.

Indrajit Bhattacharya, Louis Licamele, and Lise Getoor. Query-Time Entity Resolution. International Conference on Knowledge Discovery and Data Mining (KDD). 2006.

Indrajit Bhattacharya, Louis Licamele, and Lise Getoor. Relational Clustering for Entity Resolution Queries. International Workshop on Statistical Relational Learning (SRL). 2006.

Louis Licamele and Lise Getoor. Social Capital in Friendship-Event Networks. IEEE International Conference on Data Mining (ICDM). 2006.

2005

Marie desJardins, Priyang Rathod, and Lise Getoor. Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence. European Conference on Machine Learning (ECML). 2005.

Louis Licamele, Mustafa Bilgic, Lise Getoor, and Nick Roussopoulos. Capital and Benefit in Social Networks. Workshop on Link Analysis and Group Detection (LinkKDD). 2005.

Mustafa Bilgic, Louis Licamele, Lise Getoor, and Ben Shneiderman. D-Dupe: An Interactive Tool for Entity Resolution in Social Networks. International Symposium on Graph Drawing (GD). 2005.

Lise Getoor and Christopher Diehl. Link Mining: A Survey. SIGKDD Explorations. 2005.

Lise Getoor. Link-Based Classification. Advanced Methods for Knowledge Discovery from Complex Data. 2005.

Lisa Singh, Lise Getoor, and Louis Licamele. Pruning Social Networks Using Structural Properties and Descriptive Attributes. IEEE International Conference on Data Mining (ICDM). 2005.

Indrajit Bhattacharya and Lise Getoor. Relational Clustering for Multi-Type Entity Resolution. International Workshop on Multi-Relational Data Mining (MRDM). 2005.

2004

Indrajit Bhattacharya and Lise Getoor. Deduplication and Group Detection Using Links. Workshop on Link Analysis and Group Detection (LinkKDD). 2004.

Indrajit Bhattacharya and Lise Getoor. Iterative Record Linkage for Cleaning and Integration. SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD). 2004.

Lise Getoor, Jeanne Rhee, Daphne Koller, and Peter Small. Understanding Tuberculosis Epidemiology Using Structured Statistical Models. Artificial Intelligence in Medicine. 2004.

Indrajit Bhattacharya, Lise Getoor, and Yoshua Bengio. Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models. Annual Meeting of the Association for Computational Linguistics (ACL). 2004.

Kristina Lerman, Lise Getoor, Steven Minton, and Craig Knoblock. Using the Structure of Web Sites for Automatic Segmentation of Tables. International Conference on Management of Data (SIGMOD). 2004.

2003

Lise Getoor. Link Mining: A New Data Mining Challenge. SIGKDD Explorations. 2003.

Qing Lu and Lise Getoor. Link-Based Classification. International Conference on Machine Learning (ICML). 2003.

Qing Lu and Lise Getoor. Link-Based Classification Using Labeled and Unlabeled Data. ICML Workshop on The Continuum From Labeled to Unlabeled Data in Machine Learning and Data Mining. 2003.

Qing Lu and Lise Getoor. Link-Based Text Classification. IJCAI Workshop on Text Mining and Link Analysis (TextLink). 2003.

Edward Hung, Lise Getoor, and V. S. Subrahmanian. PXML: A Probabilistic Semistructured Data Model and Algebra. IEEE International Conference on Data Engineering (ICDE). 2003.

Edward Hung, Lise Getoor, and V. S. Subrahmanian. Probabilistic Interval XML. International Conference on Database Theory (ICDT). 2003.

Lise Getoor. Structure Discovery Using Statistical Relational Learning. IEEE Data Engineering Bulletin. 2003.

2002

Lise Getoor, Nir Friedman, Daphne Koller, and Benjamin Taskar. Learning Probabilistic Models of Link Structure. Journal of Machine Learning Research (JMLR). 2002.

Lise Getoor, Nir Friedman, and Daphne Koller. Learning Structured Statistical Models From Relational Data. Electronic Transactions on Artificial Intelligence (ETAI). 2002.

2001

Lise Getoor, Nir Friedman, Daphne Koller, and Benjamin Taskar. Learning Probabilistic Models of Relational Structure. International Conference on Machine Learning (ICML). 2001.

Lise Getoor, Nir Friedman, Daphne Koller, and Avi Pfeffer. Learning Probabilistic Relational Models. Relational Data Mining. 2001.

Lise Getoor. Learning Statistical Models From Relational Data. Stanford. 2001.

Lise Getoor. Multi-Relational Data Mining Using Probabilistic Models. International Workshop on Multi-Relational Data Mining (MRDM). 2001.

Lise Getoor, Eran Segal, Benjamin Taskar, and Daphne Koller. Probabilistic Models of Text and Link Structure for Hypertext Classification. IJCAI Workshop on Text Learning: Beyond Supervision. 2001.

Lise Getoor, Daphne Koller, and Benjamin Taskar. Selectivity Estimation Using Probabilistic Models. International Conference on Management of Data (SIGMOD). 2001.

2000

Lise Getoor, Daphne Koller, and Nir Friedman. From Instances to Classes in Probabilistic Relational Models. ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries. 2000.

Lise Getoor, Daphne Koller, and Nir Friedman. From Instances to Classes in Probabilistic Relational Models. ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries. 2000.

Lise Getoor, Daphne Koller, Benjamin Taskar, and Nir Friedman. Learning Probabilistic Relational Models with Structural Uncertainty. AAAI Workshop on Learning Statistical Models from Relational Data (LSMRD). 2000.

Marie desJardins, Lise Getoor, and Daphne Koller. Using Feature Hierarchies in Bayesian Network Learning. International Symposium on Abstraction, Reformulation, and Approximation (SARA). 2000.

1999

Nir Friedman and Lise Getoor. Efficient Learning Using Constrained Sufficient Statistics. International Workshop on Artificial Intelligence and Statistics (AISTATS). 1999.

Nir Friedman, Lise Getoor, Daphne Koller, and Avi Pfeffer. Learning Probabilistic Relational Models. International Joint Conference on Artificial Intelligence (IJCAI). 1999.

Lise Getoor and Mehran Sahami. Using Probabilistic Relational Models for Collaborative Filtering. KDD Workshop on Web Usage Analysis and User Profiling (WebKDD). 1999.

1998

Ursulza Chajewska, Joseph Norman, and Lise Getoor. Using Classification Techniques for Utility Elicitation: A Comparison between StandardGamble and Visual Analog Scale Methods. Meeting of the Society for Medical Decision Making (SMDM). 1998.

Ursulza Chajewska, Lise Getoor, and Joseph Norman. Utility Elicitation As a Classification Problem. AAAI Spring Symposium on Interactive and Mixed Initiative Decision-Theoretic Systems. 1998.

Ursulza Chajewska, Lise Getoor, Joseph Norman, and Yuval Shahar. Utility Elicitation As a Classification Problem. Conference on Uncertainty in Artificial Intelligence (UAI). 1998.

1997

Lise Getoor, Gregor Ottosson, Markus Fromherz, and Bjorn Carlson. Effictive Redundant Constraints for Online Scheduling. AAAI Conference on Artificial Intelligence (AAAI). 1997.

Lise Getoor and Markus Fromherz. Online Scheduling for Reprographic Machines. AAAI Workshop on Online Search. 1997.

1995

Amy Lansky and Lise Getoor. Scope and Abstraction: Two Criteria for Localized Planning. International Joint Conference on Artificial Intelligence (IJCAI). 1995.

Amy Lansky, Mark Friedman, Lise Getoor, Scott Schmidler, and Nick Short Jr.. The Collage/Khoros Link: Planning for Image Processing Tasks. AAAI Spring Symposium on Integrated Planning Applications. 1995.

1994

Amy Lansky and Lise Getoor. Practical Planning in COLLAGE. AAAI Fall Symposium on Planning and Learning: On to Real Applications. 1994.