Getoor, Lise

56 publications

ICML 2024 Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning Charles Andrew Dickens, Changyu Gao, Connor Pryor, Stephen Wright, Lise Getoor

ICML 2023 ESC: Exploration with Soft Commonsense Constraints for Zero-Shot Object Navigation Kaiwen Zhou, Kaizhi Zheng, Connor Pryor, Yilin Shen, Hongxia Jin, Lise Getoor, Xin Eric Wang

IJCAI 2023 NeuPSL: Neural Probabilistic Soft Logic Connor Pryor, Charles Dickens, Eriq Augustine, Alon Albalak, William Yang Wang, Lise Getoor

MLJ 2022 A Taxonomy of Weight Learning Methods for Statistical Relational Learning Sriram Srinivasan, Charles Dickens, Eriq Augustine, Golnoosh Farnadi, Lise Getoor

UAI 2022 Learning Explainable Templated Graphical Models Varun Embar, Sriram Srinivasa, Lise Getoor

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

ICML 2021 Context-Aware Online Collective Inference for Templated Graphical Models Charles Dickens, Connor Pryor, Eriq Augustine, Alexander Miller, Lise Getoor

NeurIPS 2021 Local Explanation of Dialogue Response Generation Yi-Lin Tuan, Connor Pryor, Wenhu Chen, Lise Getoor, William Yang Wang

AAAI 2020 BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic Sriram Srinivasan, Golnoosh Farnadi, Lise Getoor

AAAI 2020 Tandem Inference: An Out-of-Core Streaming Algorithm for Very Large-Scale Relational Inference Sriram Srinivasan, Eriq Augustine, Lise Getoor

IJCAI 2019 Estimating Causal Effects of Tone in Online Debates Dhanya Sridhar, Lise Getoor

AAAI 2019 Lifted Hinge-Loss Markov Random Fields Sriram Srinivasan, Behrouz Babaki, Golnoosh Farnadi, Lise Getoor

IJCAI 2018 Scalable Probabilistic Causal Structure Discovery Dhanya Sridhar, Jay Pujara, Lise Getoor

IJCAI 2017 Disambiguating Energy Disaggregation: A Collective Probabilistic Approach Sabina Tomkins, Jay Pujara, Lise Getoor

JMLR 2017 Hinge-Loss Markov Random Fields and Probabilistic Soft Logic Stephen H. Bach, Matthias Broecheler, Bert Huang, Lise Getoor

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

JMLR 2016 Stability and Generalization in Structured Prediction Ben London, Bert Huang, Lise Getoor

UAI 2015 Budgeted Online Collective Inference Jay Pujara, Ben London, Lise Getoor

ICML 2015 HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, Yan Liu

ICML 2015 Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models James Foulds, Shachi Kumar, Lise Getoor

MLJ 2015 Lifted Graphical Models: A Survey Angelika Kimmig, Lilyana Mihalkova, Lise Getoor

ICML 2015 Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen Bach, Bert Huang, Jordan Boyd-Graber, Lise Getoor

AAAI 2015 Planned Protest Modeling in News and Social Media Sathappan Muthiah, Bert Huang, Jaime Arredondo, David Mares, Lise Getoor, Graham Katz, Naren Ramakrishnan

ICML 2015 The Benefits of Learning with Strongly Convex Approximate Inference Ben London, Bert Huang, Lise Getoor

AISTATS 2015 Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees Stephen H. Bach, Bert Huang, Lise Getoor

AAAI 2014 Learning Latent Engagement Patterns of Students in Online Courses Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daumé Iii, Lise Getoor

AISTATS 2014 PAC-Bayesian Collective Stability Ben London, Bert Huang, Ben Taskar, Lise Getoor

CVPRW 2013 Collective Activity Detection Using Hinge-Loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry S. Davis

ICML 2013 Collective Stability in Structured Prediction: Generalization from One Example Ben London, Bert Huang, Ben Taskar, Lise Getoor

UAI 2013 Hinge-Loss Markov Random Fields: Convex Inference for Structured Prediction Stephen H. Bach, Bert Huang, Ben London, Lise Getoor

NeurIPS 2012 Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization Stephen Bach, Matthias Broecheler, Lise Getoor, Dianne O'leary

IJCAI 2011 Active Surveying: A Probabilistic Approach for Identifying Key Opinion Leaders Hossam Sharara, Lise Getoor, Myra Norton

ICML 2011 Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011 Lise Getoor, Tobias Scheffer

JAIR 2011 Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition Mustafa Bilgic, Lise Getoor

AAAI 2010 Active Inference for Collective Classification Mustafa Bilgic, Lise Getoor

ICML 2010 Active Learning for Networked Data Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor

NeurIPS 2010 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning Matthias Broecheler, Lise Getoor

ECML-PKDD 2010 Learning Algorithms for Link Prediction Based on Chance Constraints Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lise Getoor

UAI 2010 Probabilistic Similarity Logic Matthias Bröcheler, Lilyana Mihalkova, Lise Getoor

UAI 2009 Bisimulation-Based Approximate Lifted Inference Prithviraj Sen, Amol Deshpande, Lise Getoor

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

AAAI 2007 Online Collective Entity Resolution Indrajit Bhattacharya, Lise Getoor

JAIR 2007 Query-Time Entity Resolution Indrajit Bhattacharya, Lise Getoor

AAAI 2007 Relationship Identification for Social Network Discovery Christopher P. Diehl, Galileo Namata, Lise Getoor

AAAI 2007 VOILA: Efficient Feature-Value Acquisition for Classification Mustafa Bilgic, Lise Getoor

ICML 2006 Cost-Sensitive Learning with Conditional Markov Networks Prithviraj Sen, Lise Getoor

ICML 2006 Inferring Organizational Titles in Online Communication Galileo Mark S. Namata Jr., Lise Getoor, Christopher P. Diehl

MLJ 2006 PRL: A Probabilistic Relational Language Lise Getoor, John Grant

ECML-PKDD 2005 Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence Marie desJardins, Priyang Rathod, Lise Getoor

ICML 2003 Link-Based Classification Qing Lu, Lise Getoor

ICML 2001 Learning Probabilistic Models of Relational Structure Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar

AISTATS 1999 Efficient Learning Using Constrained Sufficient Statistics Nir Friedman, Lise Getoor

IJCAI 1999 Learning Probabilistic Relational Models Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer

UAI 1998 Utility Elicitation as a Classification Problem Urszula Chajewska, Lise Getoor, Joseph Norman, Yuval Shahar

AAAI 1997 Effective Redundant Constraints for Online Scheduling Lise Getoor, Greger Ottosson, Markus P. J. Fromherz, Björn Carlson

IJCAI 1995 Scope and Abstraction: Two Criteria for Localized Planning Amy L. Lansky, Lise Getoor