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2016

Sridhar, D. & Getoor, L. Probabilistic Inference for Causal Structure Discovery. Uncertainty in Artificial Intelligence (UAI) Workshop on Causation (2016).

sridhar-uai-open-problem-v2.pdf (118.31 KB)

Pujara, J. Probabilistic Models for Scalable Knowledge Graph Construction. (2016).

pujara-thesis15.pdf (1.06 MB)

Rekatsinas, T., Deshpande, A., Dong, X. Luna, Getoor, L. & Srivastava, D. SourceSight: Enabling Effective Source Selection. ACM SIGMOD Conference (2016).

modde087.pdf (799.94 KB)

London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. Journal of Machine Learning Research 17, (2016).

london-jlmr17.pdf (532.8 KB)

Kumar, S. et al. Unsupervised Models for Predicting Strategic Relations between Organizations. IEEE ACM International Conference on Advances in Social Networks Analysis and Mining (IEEE, 2016).

kumar_asonam16.pdf (212.61 KB)

2015

London, B., Huang, B. & Getoor, L. The Benefits of Learning with Strongly Convex Approximate Inference. International Conference on Machine Learning (ICML) (2015).

london-icml15.pdf (788.06 KB)

Pujara, J., London, B. & Getoor, L. Budgeted Online Collective Inference. Uncertainty in Artificial Intelligence (2015).

pujara-uai15.pdf (302.63 KB)

Namata, G. Mark, London, B. & Getoor, L. Collective Graph Identification. ACM Transactions on Knowledge Discovery from Data 10, 25:1–25:36 (2015).

namata-tkdd.pdf (500.96 KB)

Fakhraei, S., Foulds, J., Shashanka, M. & Getoor, L. Collective Spammer Detection in Evolving Multi-Relational Social Networks. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (ACM, 2015).

fakhraei-kdd2015.pdf (573.89 KB)

Fakhraei, S., Onukwugha, E. & Getoor, L. Healthcare Data Analytics (Reddy, C. C. Aggarwa) (CRC Press, 2015).

fakhraei_book_2015.pdf (234.2 KB)

Rekatsinas, T., Dong, X. Luna, Getoor, L. & Srivastava, D. Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration. 7th Biennial Conference on Innovative Data Systems Research (CIDR `15) (2015).

rekatsinasCIDR15.pdf (396.99 KB)

He, X., Rekatsinas, T., Foulds, J., Getoor, L. & Liu, Y. HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades. International Conference on Machine Learning (2015).

He2015HawkesTopic.pdf (819.91 KB)

Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. ArXiv:1505.04406 [cs.LG] (2015).

bach-arxiv15.pdf (686.27 KB)

Bach, S. H. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic: A Scalable Approach to Structured Prediction. (2015).

bach-thesis15.pdf (1.17 MB)

Kouki, P., Fakhraei, S., Foulds, J., Eirinaki, M. & Getoor, L. HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems. 9th ACM Conference on Recommender Systems (RecSys) (ACM, 2015).

kouki-recsys15.pdf (1.03 MB)

Sridhar, D., Foulds, J., Walker, M., Huang, B. & Getoor, L. Joint Models of Disagreement and Stance in Online Debate. Annual Meeting of the Association for Computational Linguistics (ACL) (2015).

sridhar-acl15.pdf (227.14 KB)

Foulds, J., Kumar, S. & Getoor, L. Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models. International Conference on Machine Learning (ICML) (2015).

Foulds2015LatentTopicNetworks.pdf (382.53 KB)

Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning Journal 99, 1–45 (2015).

kimmig-mlj15.pdf (785.58 KB)

Pujara, J., London, B., Getoor, L. & Cohen, W. Online Inference for Knowledge Graph Construction. Workshop on Statistical Relational AI (2015).

pujara-starai15.pdf (340.95 KB)

Bach, S. H., Huang, B., Boyd-Graber, J. & Getoor, L. Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. International Conference on Machine Learning (ICML) (2015).

bach-icml15.pdf (356.46 KB)

Rekatsinas, T. Quality-Aware Data Source Management. (2015).

Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. RELLY: Inferring Hypernym Relationships Between Relational Phrases. Conference on Empirical Methods in Natural Language Processing (2015).

agrycner-emnlp15.pdf (234.86 KB)

Rekatsinas, T. et al. SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources. 2015 SIAM International Conference on Data Mining (SDM15) (SIAM, 2015).

rekatsinasSDM2015.pdf (303.08 KB)

London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. – (2015).

london-stability15.pdf (532.16 KB)

London, B. On the Stability of Structured Prediction. (2015).

blondon-thesis.pdf (1.16 MB)

Farnadi, G. et al. Statistical Relational Learning with Soft Quantifiers. International Conference on Inductive Logic Programming (ILP) (2015).

farnadi-ilp15.pdf (578.43 KB)

Ramesh, A., Rodriguez, M. & Getoor, L. Understanding Influence in Online Professional Networks. NIPS Workshop on Networks in Social and Information Sciences (2015).

ramesh-nipsws15.pdf (211.44 KB)

Bach, S. H., Huang, B. & Getoor, L. Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees. Artificial Intelligence and Statistics (AISTATS) (2015).

bach-aistats15.pdf (345.2 KB)

Pujara, J., Miao, H., Getoor, L. & Cohen, W. Using Semantics & Statistics to Turn Data into Knowledge. AI Magazine 36, 65–74 (2015).

pujara_aimag15.pdf (359.48 KB)

Ramesh, A., Kumar, S., Foulds, J. & Getoor, L. Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums. 53rd Annual Meeting of the Association for Computational Linguistics (ACL) (2015).

ramesh-acl15.pdf (168.7 KB)

2014

Ramakrishnan, N. et al. ‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2014).

ramakrishnan-kdd14.pdf (1.15 MB)

Pujara, J. & Getoor, L. Building Dynamic Knowledge Graphs. NIPS Workshop on Automated Knowledge Base Construction (2014).

pujara_akbc14.pdf (143.26 KB)

Sridhar, D., Getoor, L. & Walker, M. Collective Stance Classification of Posts in Online Debate Forums. ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media (2014).

sridhar-aclws14.pdf (190.8 KB)

Sridhar, D., Foulds, J., Huang, B., Walker, M. & Getoor, L. Collective classification of stance and disagreement in online debate forums. Bay Area Machine Learning Symposium (BayLearn) (2014).

Fakhraei, S., Onukwugha, E. & Getoor, L. Healthcare Data Analytics (Reddy, C. C. Aggarwa) (CRC Press, 2014).

Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Extending PSL with Fuzzy Quantifiers. International Workshop on Statistical Relational Artificial Intelligence (StaRAI) (2014).

farnadi-starai14.pdf (196.15 KB)

Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Learning Latent Engagement Patterns of Students in Online Courses. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI Press, 2014).

ramesh-aaai14.pdf (505.47 KB)

Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning 1-45 (2014).

Fakhraei, S., Huang, B., Raschid, L. & Getoor, L. Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2014).

fakhraei-tcbb2014_accepted.pdf (3.97 MB)

London, B., Huang, B., Taskar, B. & Getoor, L. PAC-Bayesian Collective Stability. Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (2014).

london-aistats14.pdf (490.14 KB)

Bach, S. H., Huang, B. & Getoor, L. Probabilistic Soft Logic for Social Good. KDD Workshop on Data Science for Social Good (2014).

bach-dssg14.pdf (124.88 KB)

Bach, S. H., Huang, B. & Getoor, L. Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies. NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML) (2014).

bach-discml14.pdf (254.9 KB)

London, B., Huang, B. & Getoor, L. On the Strong Convexity of Variational Inference. NIPS Workshop on Advances in Variational Inference (2014).

london-nips14ws.pdf (253.72 KB)

Moustafa, W. Eldin, Kimmig, A., Deshpande, A. & Getoor, L. Subgraph Pattern Matching over Uncertain Graphs with Identity Linkage Uncertainty. International Conference on Data Engineering (ICDE) (2014).

ICDE14_conf_full_374.pdf (1.57 MB)

Bradley, S. & Getoor, L. Topic Modeling for Wikipedia Link Disambiguation. ACM Transactions on Information Systems 32, (2014).

Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs. ACM Conference on Learning at Scale (ACM, 2014).

Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Understanding MOOC Discussion Forums using Seeded LDA. 9th ACL Workshop on Innovative Use of NLP for Building Educational Applications (ACL, 2014).

ramesh-aclws14.pdf (137.57 KB)

Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases. NIPS Workshop on Automated Knowledge Base Construction (2014).

2013

London, B. et al. Collective Activity Detection using Hinge-loss Markov Random Fields. CVPR Workshop on Structured Prediction: Tractability, Learning and Inference (2013).

london-cvpr13.pdf (705.87 KB)

London, B. & Getoor, L. Data Classification: Algorithms and Applications (Aggarwal, C.) (CRC Press, 2013).

cc-chapter.pdf (394.37 KB)

Pages