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HyperFair: A Soft Approach to Integrating Fairness Criteria

Sep 05, 2020
Charles Dickens, Rishika Singh, Lise Getoor


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Causal Relational Learning

Apr 07, 2020
Babak Salimi, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, Dan Suciu


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Estimating Aggregate Properties In Relational Networks With Unobserved Data

Jan 27, 2020
Varun Embar, Sriram Srinivasan, Lise Getoor


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User Profiling Using Hinge-loss Markov Random Fields

Jan 05, 2020
Golnoosh Farnadi, Lise Getoor, Marie-Francine Moens, Martine De Cock


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Estimating Causal Effects of Tone in Online Debates

Jun 12, 2019
Dhanya Sridhar, Lise Getoor

* Accepted at International Joint Conference on Artificial Intelligence (IJCAI) 2019 for oral presentation 

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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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A Fairness-aware Hybrid Recommender System

Sep 13, 2018
Golnoosh Farnadi, Pigi Kouki, Spencer K. Thompson, Sriram Srinivasan, Lise Getoor


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Scalable Structure Learning for Probabilistic Soft Logic

Jul 03, 2018
Varun Embar, Dhanya Sridhar, Golnoosh Farnadi, Lise Getoor

* 8 pages, 2 figures 

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Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

Nov 17, 2017
Stephen H. Bach, Matthias Broecheler, Bert Huang, Lise Getoor

* Journal of Machine Learning Research (JMLR), 18(109):1-67, 2017 

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Using Noisy Extractions to Discover Causal Knowledge

Nov 16, 2017
Dhanya Sridhar, Jay Pujara, Lise Getoor


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A Collective, Probabilistic Approach to Schema Mapping: Appendix

Feb 11, 2017
Angelika Kimmig, Alex Memory, Renee J. Miller, Lise Getoor

* This is the appendix to the paper "A Collective, Probabilistic Approach to Schema Mapping" accepted to ICDE 2017 

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Generic Statistical Relational Entity Resolution in Knowledge Graphs

Jul 04, 2016
Jay Pujara, Lise Getoor

* In the Sixth International Workshop on Statistical Relational AI, 2016 

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Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks

Jul 02, 2016
Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, Lise Getoor

* Presented at SIGKDD 12th International Workshop on Mining and Learning with Graphs (MLG'16) 

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Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition

Jan 16, 2014
Mustafa Bilgic, Lise Getoor

* Journal Of Artificial Intelligence Research, Volume 41, pages 69-95, 2011 

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Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction

Sep 26, 2013
Stephen Bach, Bert Huang, Ben London, Lise Getoor

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

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A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization

Aug 30, 2013
Hui Miao, Xiangyang Liu, Bert Huang, Lise Getoor


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Graph-based Generalization Bounds for Learning Binary Relations

May 31, 2013
Ben London, Bert Huang, Lise Getoor


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Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss

May 31, 2013
Ben London, Theodoros Rekatsinas, Bert Huang, Lise Getoor


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Scalable Text and Link Analysis with Mixed-Topic Link Models

Mar 28, 2013
Yaojia Zhu, Xiaoran Yan, Lise Getoor, Cristopher Moore

* Proc. 19th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2013, 473-481 
* 11 pages, 4 figures 

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Utility Elicitation as a Classification Problem

Jan 30, 2013
Urszula Chajewska, Lise Getoor, Joseph Norman, Yuval Shahar

* Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998) 

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LA-LDA: A Limited Attention Topic Model for Social Recommendation

Jan 26, 2013
Jeon-Hyung Kang, Kristina Lerman, Lise Getoor

* The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) 

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Bisimulation-based Approximate Lifted Inference

May 09, 2012
Prithviraj Sen, Amol Deshpande, Lise Getoor

* Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI2009) 

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Probabilistic Similarity Logic

Mar 15, 2012
Matthias Brocheler, Lilyana Mihalkova, Lise Getoor

* Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010) 

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Lifted Graphical Models: A Survey

Aug 26, 2011
Lilyana Mihalkova, Lise Getoor


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A Probabilistic Approach for Learning Folksonomies from Structured Data

Nov 16, 2010
Anon Plangprasopchok, Kristina Lerman, Lise Getoor

* In Proceedings of the 4th ACM Web Search and Data Mining Conference (WSDM) 

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Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata

May 27, 2010
Anon Plangprasopchok, Kristina Lerman, Lise Getoor

* 10 pages, To appear in the Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD) 2010 

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Integrating Structured Metadata with Relational Affinity Propagation

May 26, 2010
Anon Plangprasopchok, Kristina Lerman, Lise Getoor

* 6 Pages, To appear at AAAI Workshop on Statistical Relational AI 

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