Publications

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2013
J. Kang, Lerman, K., and Getoor, L., LA-LDA: A Limited Attention Topic Model for Social Recommendation, in The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013), 2013.PDF icon kang-sbp13.pdf (622.52 KB)
J. Pujara, Miao, H., Getoor, L., and Cohen, W., Large-Scale Knowledge Graph Identification using PSL, in ICML Workshop on Structured Learning (SLG), 2013.PDF icon pujara_slg13.pdf (277.63 KB)
J. Pujara, Miao, H., Getoor, L., and Cohen, W., Large-Scale Knowledge Graph Identification using PSL, in AAAI Fall Symposium on Semantics for Big Data, 2013.PDF icon pujara_s4bd13.pdf (306.96 KB)
S. H. Bach, Huang, B., and Getoor, L., Large-margin Structured Learning for Link Ranking, in NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications, 2013.PDF icon bach-fna13.pdf (210.09 KB)
S. H. Bach, Huang, B., and Getoor, L., Learning Latent Groups with Hinge-loss Markov Random Fields, in ICML Workshop on Inferning: Interactions between Inference and Learning, 2013.PDF icon bach-inferning13.pdf (348.79 KB)
A. Ramesh, Goldwasser, D., Huang, B., III, H. Daume, and Getoor, L., Modeling Learner Engagement in MOOCs using Probabilistic Soft Logic, in NIPS Workshop on Data Driven Education, 2013.PDF icon ramesh-nipsws13.pdf (153.92 KB)
B. London, Rekatsinas, T., Huang, B., and Getoor, L., Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss. University of Maryland College Park, 2013.PDF icon mrwtd.pdf (460.45 KB)
J. Pujara, Miao, H., Getoor, L., and Cohen, W., Ontology-Aware Partitioning for Knowledge Graph Identification, in CIKM Workshop on Automatic Knowledge Base Construction, 2013.PDF icon pujara_akbc13.pdf (370.62 KB)
B. London, Huang, B., Taskar, B., and Getoor, L., PAC-Bayes Generalization Bounds for Randomized Structured Prediction, in NIP Workshop on Perturbation, Optimization and Statistics, 2013.PDF icon london-nips13ws.pdf (205.57 KB)
2014
A. Grycner, Weikum, G., Pujara, J., Foulds, J., and Getoor, L., A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases, in NeurIPS, 2014.
N. Ramakrishnan, Butler, P., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena, J., Vullikanti, A., Korkmaz, G., Kuhlman, C., Marathe, A., Zhao, L., Ting, H., Huang, B., Srinivasan, A., Trinh, K., Getoor, L., Katz, G., Doyle, A., Ackermann, C., Zavorin, I., Ford, J., Summers, K., Fayed, Y., Arredondo, J., Gupta, D., and Mares, D., ‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2014.PDF icon ramakrishnan-kdd14.pdf (1.15 MB)
J. Pujara and Getoor, L., Building Dynamic Knowledge Graphs, in NIPS Workshop on Automated Knowledge Base Construction, 2014.PDF icon pujara_akbc14.pdf (143.26 KB)
D. Sridhar, Getoor, L., and Walker, M., Collective Stance Classification of Posts in Online Debate Forums, in ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media, 2014.PDF icon sridhar-aclws14.pdf (190.8 KB)
D. Sridhar, Foulds, J., Huang, B., Walker, M., and Getoor, L., Collective classification of stance and disagreement in online debate forums, in Bay Area Machine Learning Symposium (BayLearn), 2014.
G. Farnadi, Bach, S. H., Moens, M. - F., Getoor, L., and De Cock, M., Extending PSL with Fuzzy Quantifiers, in International Workshop on Statistical Relational Artificial Intelligence (StaRAI), 2014.PDF icon farnadi-starai14.pdf (196.15 KB)
A. Ramesh, Goldwasser, D., Huang, B., III, H. Daume, and Getoor, L., Learning Latent Engagement Patterns of Students in Online Courses, in Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014.PDF icon ramesh-aaai14.pdf (505.47 KB)
A. Kimmig, Mihalkova, L., and Getoor, L., Lifted graphical models: a survey, Machine Learning, pp. 1-45, 2014.
S. Fakhraei, Huang, B., Raschid, L., and Getoor, L., Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2014.PDF icon fakhraei-tcbb2014_accepted.pdf (3.97 MB)
B. London, Huang, B., Taskar, B., and Getoor, L., PAC-Bayesian Collective Stability, in Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 2014.PDF icon london-aistats14.pdf (490.14 KB)
S. H. Bach, Huang, B., and Getoor, L., Probabilistic Soft Logic for Social Good, in KDD Workshop on Data Science for Social Good, 2014.PDF icon bach-dssg14.pdf (124.88 KB)
S. H. Bach, Huang, B., and Getoor, L., Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies, in NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML), 2014.PDF icon bach-discml14.pdf (254.9 KB)
B. London, Huang, B., and Getoor, L., On the Strong Convexity of Variational Inference, in NIPS Workshop on Advances in Variational Inference, 2014.PDF icon london-nips14ws.pdf (253.72 KB)
W. Eldin Moustafa, Kimmig, A., Deshpande, A., and Getoor, L., Subgraph Pattern Matching over Uncertain Graphs with Identity Linkage Uncertainty, in International Conference on Data Engineering (ICDE), 2014.PDF icon ICDE14_conf_full_374.pdf (1.57 MB)
S. Bradley and Getoor, L., Topic Modeling for Wikipedia Link Disambiguation, ACM Transactions on Information Systems, vol. 32, 2014.
A. Ramesh, Goldwasser, D., Huang, B., III, H. Daume, and Getoor, L., Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs, in ACM Conference on Learning at Scale, 2014.
A. Ramesh, Goldwasser, D., Huang, B., Daume, III, H., and Getoor, L., Understanding MOOC Discussion Forums using Seeded LDA, in ACL Workshop on Innovative Use of NLP for Building Educational Applications, 2014.PDF icon ramesh-aclws14.pdf (137.57 KB)
2015
J. Pujara, London, B., and Getoor, L., Budgeted Online Collective Inference, in UAI, 2015.PDF icon pujara-uai15.pdf (302.63 KB)
G. Namata, London, B., and Getoor, L., Collective Graph Identification, TKDD, vol. 10, 2015.PDF icon namata-tkdd15.pdf (500.96 KB)
S. Fakhraei, Foulds, J., Shashanka, M., and Getoor, L., Collective Spammer Detection in Evolving Multi-Relational Social Networks, in KDD, 2015.PDF icon fakhraei-kdd2015.pdf (573.89 KB)
S. Fakhraei, Onukwugha, E., and Getoor, L., Data Analytics for Pharmaceutical Discoveries, 1st ed., vol. 1. CRC Press, 2015, p. 1--25.PDF icon fakhraei-book15.pdf (234.2 KB)
T. Rekatsinas, Dong, X. Luna, Getoor, L., and Srivastava, D., Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration, in 7th Biennial Conference on Innovative Data Systems Research (CIDR `15), 2015.PDF icon rekatsinasCIDR15.pdf (396.99 KB)
T. Rekatsinas, Ghosh, S., Mekaru, S., Nsoesie, E., Brownstein, J., Getoor, L., and Ramakrishnan, N., Forecasting Rare Disease Outbreaks Using Multiple Data Sources, STAT ANAL DATA MIN, 2015.
X. He, Rekatsinas, T., Foulds, J., Getoor, L., and Liu, Y., HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades, in International Conference on Machine Learning, 2015.PDF icon He2015HawkesTopic.pdf (819.91 KB)
S. H. Bach, Broecheler, M., Huang, B., and Getoor, L., Hinge-Loss Markov Random Fields and Probabilistic Soft Logic, ArXiv:1505.04406 [cs.LG], 2015.PDF icon bach-arxiv15.pdf (686.27 KB)
P. Kouki, Fakhraei, S., Foulds, J., Eirinaki, M., and Getoor, L., HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems, in 9th ACM Conference on Recommender Systems (RecSys), 2015.PDF icon kouki-recsys15.pdf (1.03 MB)
D. Sridhar, Foulds, J., Walker, M., Huang, B., and Getoor, L., Joint Models of Disagreement and Stance in Online Debate, in Annual Meeting of the Association for Computational Linguistics (ACL), 2015.PDF icon sridhar-acl15.pdf (227.14 KB)
J. Foulds, Kumar, S., and Getoor, L., Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models, in International Conference on Machine Learning (ICML), 2015.PDF icon Foulds2015LatentTopicNetworks.pdf (382.53 KB)
A. Kimmig, Mihalkova, L., and Getoor, L., Lifted graphical models: a survey, Machine Learning Journal, vol. 99, pp. 1–45, 2015.PDF icon kimmig-mlj15.pdf (785.58 KB)
J. Pujara, London, B., Getoor, L., and Cohen, W., Online Inference for Knowledge Graph Construction., in Workshop on Statistical Relational AI, 2015.PDF icon pujara-starai15.pdf (340.95 KB)
S. H. Bach, Huang, B., Boyd-Graber, J., and Getoor, L., Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs, in International Conference on Machine Learning (ICML), 2015.PDF icon bach-icml15.pdf (356.46 KB)
A. Grycner, Weikum, G., Pujara, J., Foulds, J., and Getoor, L., RELLY: Inferring Hypernym Relationships Between Relational Phrases, in Conference on Empirical Methods in Natural Language Processing, 2015.PDF icon agrycner-emnlp15.pdf (234.86 KB)
T. Rekatsinas, Ghosh, S., Mekaru, S., Nsoesie, E., Brownstein, J., Getoor, L., and Ramakrishnan, N., SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources, in 2015 SIAM International Conference on Data Mining (SDM15), 2015.PDF icon rekatsinasSDM2015.pdf (303.08 KB)
B. London, Huang, B., and Getoor, L., Stability and Generalization in Structured Prediction, , 2015.PDF icon london-stability15.pdf (532.16 KB)
G. Farnadi, Bach, S. H., Blondeel, M., Moens, M. - F., Getoor, L., and De Cock, M., Statistical Relational Learning with Soft Quantifiers, in International Conference on Inductive Logic Programming (ILP), 2015.PDF icon farnadi-ilp15.pdf (578.43 KB)
B. London, Huang, B., and Getoor, L., The Benefits of Learning with Strongly Convex Approximate Inference, in ICML, 2015.PDF icon london-icml15.pdf (788.06 KB)
A. Ramesh, Rodriguez, M., and Getoor, L., Understanding Influence in Online Professional Networks, in NIPS Workshop on Networks in Social and Information Sciences, 2015.PDF icon ramesh-nipsws15.pdf (211.44 KB)
S. H. Bach, Huang, B., and Getoor, L., Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees, in Artificial Intelligence and Statistics (AISTATS), 2015.PDF icon bach-aistats15.pdf (345.2 KB)
J. Pujara, Miao, H., Getoor, L., and Cohen, W., Using Semantics & Statistics to Turn Data into Knowledge, AI Magazine, vol. 36, pp. 65–74, 2015.PDF icon pujara_aimag15.pdf (359.48 KB)
A. Ramesh, Kumar, S., Foulds, J., and Getoor, L., Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums, in 53rd Annual Meeting of the Association for Computational Linguistics (ACL), 2015.PDF icon ramesh-acl15.pdf (168.7 KB)

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