Publications


General

Biba, Marenglen (2009). Integrating Logic and Probability: Algorithmic Improvements in Markov Logic Networks. PhD Thesis. University of Bari, 2009.

Domingos, Pedro and Kok, Stanley and Poon, Hoifung and Richardson, Matt and Singla, Parag (2006). Unifying Logical and Statistical AI. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (pp. 2-7), 2006. Boston, MA: AAAI Press.

Domingos, Pedro (2006). What's Missing in AI: The Interface Layer. In P. Cohen (ed.), Artificial Intelligence: The First Hundred Years. Menlo Park, CA: AAAI Press.

Domingos, Pedro (2007a). Toward Knowledge-Rich Data Mining. Data Mining and Knowledge Discovery, 15, 21-28, 2007.

Domingos, Pedro (2007b). Structured Machine Learning: Ten Problems for the Next Ten Years. In Proceedings of Seventeenth International Conference on Inductive Logic Programming, 2007. Corvallis, Oregon: Springer.

Domingos, Pedro and Richardson, Matthew (2007). Markov Logic: A Unifying Framework for Statistical Relational Learning. In L. Getoor and B. Taskar (eds.), Introduction to Statistical Relational Learning (pp. 339-371), 2007. Cambridge, MA: MIT Press.

Domingos, Pedro and Kok, Stanley and Lowd, Daniel and Poon, Hoifung and Richardson, Matthew and Singla, Parag (2007). Markov Logic. In L. De Raedt, P. Frasconi, K. Kersting and S. Muggleton (eds.), Probabilistic Inductive Logic Programming. New York: Springer.

Domingos, Pedro and Lowd, Daniel (2008). Markov Logic: An Interface Layer for AI . Morgan & Claypool, 2009.

Domingos, Pedro and Lowd, Daniel (2019). Unifying Logical and Statistical AI with Markov Logic, Communications of the ACM, 62 (7), 74-83, 2019.

Jain, Dominik and Kirchlechner, Bernhard and Beetz, Michael (2007). Extending Markov Logic to Model Probability Distributions in Relational Domains. In Proceedings of the 30th German Conference on Artificial Intelligence (KI-2007) (pp. 129-143), 2007.

Lowd, Daniel and Domingos, Pedro (2007a). Recursive Random Fields. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (pp. 950-955), 2007. Hyderabad, India: AAAI Press.

Mihalkova, Lily (2009). Learning with Markov Logic Networks: Transfer Learning, Structure Learning, and an Application to Web Query Disambiguation. PhD Thesis. University of Texas, Austin, 2009.

Nath, Aniruddh and Domingos, Pedro (2009). A Language for Relational Decision Theory. In Proceedings of the Sixth International Workshop on Statistical Relational Learning, 2009. Leuven, Belgium.

Nath, Aniruddh and Richardson, Matthew (2012). Counting-MLNs: Learning Relational Structure for Decision Making. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012). Toronto, Ontario, Canada.

Papai, Tivadar and Kautz, Henry and Stefankovic, Daniel (2012). Slice Normalized Dynamic Markov Logic Networks. In Advances in Neural Information Processing Systems 25 (NIPS-2012). Lake Tahoe, Nevada.

Richardson, Matt and Domingos, Pedro (2006). Markov Logic Networks. Machine Learning, 62, 107-136, 2006.

Singla, Parag and Domingos, Pedro (2007). Markov Logic in Infinite Domains. In Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (pp. 368-375), 2007. Vancouver, Canada: AUAI Press.

Singla, Parag (2009). Markov Logic: Theory, Algorithms and Applications. PhD Thesis. University of Washington, Seattle, 2009.

Torrey, Lisa (2009). Relational Transfer in Reinforcement Learning. PhD Thesis. University of Wisconsin-Madison, 2009.

Wang, Jue and Domingos, Pedro (2008). Hybrid Markov Logic Networks. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008. Chicago, IL.


Inference

Andrzejewski, David and Zhu, Xiaojin and Craven, Mark and Benjamin Recht (2011). A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation Using First-Order Logic. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI-2011). Barcelona, Spain.

Apsel, Udi and Brafman, Ronen I. (2012). Lifted MEU by Weighted Model Counting. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012). Toronto, Ontario, Canada.

Gonzalez, Joseph and Low, Yucheng and Guestrin, Carlos and O'Hallaron, David (2009). Distributed Parallel Inference on Large Factor Graphs. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, 2009. Montreal, Canada.

Kersting, K. and Ahmadi, B. and Natarajan, S. (2009). Counting Belief Propagation. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, 2009. Montreal, Canada.

Mihalkova, Lily and Richardson, Matthew (2007). Speeding up Inference in Statistical Relational Learning by Clustering Similar Query Literals. MSR-TR-2008-72.

Niu, Feng and Re, Christopher and Doan, AnHai and Shavlik (2011). Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS. In Proceedings of the 37th International Conference on Very Large Data Bases (VLDB 2011), Seattle, Washington.

Poon, Hoifung and Domingos, Pedro (2006). Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (pp. 458-463), 2006. Boston, MA: AAAI Press.

Poon, Hoifung and Domingos, Pedro and Sumner, Marc (2008). A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008 (AAAI-08). Chicago, IL: AAAI Press.

Riedel, Sebastian (2008). Improving the Accuracy and Efficiency of MAP Inference for Markov Logic. In Proceedings of UAI 2008.

Riedel, Sebastian (2009). Cutting Plane MAP Inference for Markov Logic. SRL 2009.

Shavlik, J. and Natarajan, S. (2009). Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network. In Proceedings of the Twenty-first International Joint Conference on Artificial Intelligence, 2009. Pasadena, CA.

Singla, Parag and Domingos, Pedro (2006). Memory-Efficient Inference in Relational Domains. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (pp. 488-493), 2006. Boston, MA: AAAI Press.

Singla, Parag and Domingos, Pedro (2008). Lifted First-Order Belief Propagation. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008 (AAAI-08). Chicago, IL: AAAI Press.

Weight Learning

Lowd, Daniel and Domingos, Pedro (2007b). Efficient Weight Learning for Markov Logic Networks. In Proceedings of the Eleventh European Conference on Principles and Practice of Knowledge Discovery in Databases (pp. 200-211), 2007. Warsaw, Poland: Springer.

Singla, Parag and Domingos, Pedro (2005). Discriminative Training of Markov Logic Networks. In Proceedings of the Twentieth National Conference on Artificial Intelligence (pp. 868-873), 2005. Pittsburgh, PA: AAAI Press.

Structure Learning

Biba, Marenglen and Ferilli, Stefano and Esposito, Floriana (2008a). Structure Learning of Markov Logic Networks through Iterated Local Search. In Proceedings of 18th European Conference on Artificial Intelligence (ECAI 2008), Patras, Greece.

Biba, Marenglen and Ferilli, Stefano and Esposito, Floriana (2008b). Discriminative Structure Learning of Markov Logic Networks. In Proceedings of 18th International Conference on Inductive Logic Programming, (ILP 2008), LNCS 5194, (pp. 59-76), Springer, 2008.

Dinh, Quang-Thang and Exbrayat, Matthieu and Vrain, Christel. Generative Structure Learning for Markov Logic Networks Based on Graph of Predicates. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI-2011). Barcelona, Spain.

Huynh, Tuyen N. and Mooney, Raymond J. (2008). Discriminative Structure and Parameter Learning for Markov Logic Networks. In Proceedings of the 25th International Conference on Machine Learning (ICML-08), Helsinki, Finland, July 2008.

Kok, Stanley and Domingos, Pedro (2005). Learning the Structure of Markov Logic Networks. In Proceedings of the Twenty-Second International Conference on Machine Learning (pp. 441-448), 2005. Bonn, Germany: ACM Press.

Kok, Stanley and Domingos, Pedro (2007). Statistical Predicate Invention. In Proceedings of the Twenty-Fourth International Conference on Machine Learning (pp. 433-440), 2007. Corvallis, Oregon: ACM Press.

Kok, Stanley and Domingos, Pedro (2009). Learning Markov Logic Network Structure via Hypergraph Lifting. In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Montreal, Canada: ACM Press.

Kok, Stanley and Domingos, Pedro (2010). Learning Markov Logic Networks Using Structural Motifs. In Proceedings of the Twenty-Seventh International Conference on Machine Learning, 2010. Haifa, Israel: ACM Press.

Mihalkova, Lily and Mooney, Raymond J. (2007). Bottom-Up Learning of Markov Logic Network Structure. In Proceedings of the 24th International Conference on Machine Learning (ICML-07). pp. 625-632.

Van Haaren, Jan and Davis, Jesse (2012). Markov Network Structure Learning: A Randomized Feature Generation Approach. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012). Toronto, Ontario, Canada.

Transfer Learning

Davis, Jesse and Domingos, Pedro (2009). Deep Transfer via Second-Order Markov Logic. In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Montreal, Canada: ACM Press.

Mihalkova, Lily and Huynh, Tuyen and Mooney, Raymond J. (2007). Mapping and Revising Markov Logic Networks for Transfer Learning. In Proceedings the 22nd Conference on Artificial Intelligence (AAAI-07). pp. 608-614.

Mihalkova, Lily and Mooney, Raymond J. (2008). Transfer Learning by Mapping with Minimal Target Data. In Proceedings of the AAAI-2008 Workshop on Transfer Learning for Complex Tasks, 2008. Chicago, IL: AAAI Press.

Reinforcement Learning

Torrey, L. and Shavlik, J. and Natarajan, S. and Kuppili, P. and Walker, T. (2008). Transfer in Reinforcement Learning via Markov Logic Networks. In Proceedings of the AAAI-2008 Workshop on Transfer Learning for Complex Tasks, 2008. Chicago, IL: AAAI Press.

Torrey, L. and Shavlik, J. (2009). Policy Transfer via Markov Logic Networks. In Proceedings of the Nineteenth Conference on Inductive Logic Programming, 2009. Leuven, Belgium.

Wang, Weiwei and Gao, Yang and Chen, Xingguo and Ge, Shen (2008). Reinforcement Learning with Markov Logic Networks. In Proceedings of MICAI 2008, LNAI 5317, p230-243, 2008.

Applications

Zhu, Y.; Fathi, A.; Fei-Fei, L (2014). Reasoning about Object Affordances in a Knowledge Base Representation. In Proceedings of the 13th European Conference on Computer Vision (ECCV 2014). Zurich, Switzerland.

Papadopoulos, Hélène and Tzanetakis, George (2013). Exploiting structural relationships in audio music signals using Markov Logic Networks. In Proceedings of the 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). Vancouver, Canada.

Papadopoulos, Hélène and Tzanetakis, George (2012). Modeling Chord and Key Structure with Markov Logic. In Proceedings of the 13th International Society for Music Information Retrieval Conference (ISMIR 2012). Porto, Portugal.

Che, Wanxiang and Liu, Ting (2010). Jointly Modeling WSD and SRL with Markov Logic. In Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010). Beijing, China.

Dietterich, Thomas G. and Bao, Xinlong (2008). Integrating Multiple Learning Components Through Markov Logic. In Proceedings of the Twenty-Third Conference on Artificial Intelligence (AAAI-2008).

Ha, Eun Young and Rowe, Jonathan P. and Mott, Bradford W. and Lester, James C. (2011). Goal Recognition with Markov Logic Networks for Player-Adaptive Games. In Proceedings of the Seventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-11). Stanford, California.

Hajishirzi, Hannaneh and Amir, Eyal (2008). Sampling First Order Logical Particles. In Proceedings of the 2008 International Conference on Uncertainty in Artificial Intelligence (UAI'08), 2008.

Jha, Abhay and Rastogi, Vibhor and Suciu, Dan (2008). Evaluating Queries in the Presence of Soft Key Constraints. In PODS, 2008.

Kok, Stanley and Domingos, Pedro (2008). Extracting Semantic Networks from Text via Relational Clustering. In Proceedings of the Nineteenth European Conference on Machine Learning, 2008. Antwerp, Belgium: Springer.

Kok, Stanley and Yih, Wen-tau (2009). Extracting Product Information from Email Receipts using Markov Logic. In Proceedings of the Sixth Conference on Email and Anti-Spam, 2009. Mountain View, California.

Lippi, Marco and Frasconi, Paolo (2008). Markov Logic Improves Protein β-Partners Prediction. In Proceedings of the 6th International Workshop on Mining and Learning with Graphs.

Liu, Zhao and Qiu, Xipeng and Cao, Ling and Huang, Xuanjing (2012). Discovering Logical Knowledge for Deep Question Answering. In Proceedings of 21st ACM International Conference on Information and Knowledge Management (CIKM-2012). Maui, Hawaii.

Meza-Ruiz, Ivan and Riedel, Sebastian and Lemon, Oliver (2008a). Spoken Language Understanding in dialogue systems, using a 2-layer Markov Logic Network: improving semantic accuracy. Late Breaking Abstracts of Londial '08: Workshop on the semantics and pragmatics of dialogue.

Meza-Ruiz, Ivan and Riedel, Sebastian and Lemon, Oliver (2008b). Accurate Statistical Spoken Language Understanding from Limited Development Resources. In Proceedings of ICASSP.

Meza-Ruiz, Ivan and Riedel, Sebastian (2009a). Multilingual Semantic Role Labelling with Markov Logic. CoNLL 2009 Shared Task.

Meza-Ruiz, Ivan and Riedel, Sebastian (2009b). Jointly Identifying Predicates, Arguments and Senses using Markov Logic. NAACL-HLT 2009.

Poon, Hoifung and Domingos, Pedro (2007). Joint Inference in Information Extraction. In Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence (pp. 913-918), 2007. Vancouver, Canada: AAAI Press.

Poon, Hoifung and Domingos, Pedro (2008). Joint Unsupervised Coreference Resolution with Markov Logic. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing (pp. 649-658). Honolulu, HI: ACL.

Poon, Hoifung and Domingos, Pedro (2009). Unsupervised Semantic Parsing. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Singapore: ACL. To appear.

Riedel, Sebastian and Klein, Ewan (2005). Genic Interaction Extraction with Semantic and Syntactic Chains. In Proceedings of the Learning in Logic Workshop, ICML 2005. (Winner of Learning Language in Logic Genic Interaction Challenge 2005.)

Riedel, Sebastian and Meza-Ruiz Ivan (2008). Collective Semantic Role Labelling with Markov Logic. In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning, 2008. (Winner of Open Task, CoNLL Semantic Role Labelling Shared Task 2008.)

Riedel, Sebastian and Chun, Hong-Woo and Takagi, Toshihisa and Tsujii, Jun'ichi (2009). A Markov Logic Approach to Bio-Molecular Event Extraction. BioNLP 2009 Shared Task.

Schoenmackers, Stefan and Etzioni, Oren and Weld, Daniel S. (2008). Scaling Textual Inference to the Web. In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning, 2008.

Singla, Parag and Domingos, Pedro (2006). Entity Resolution with Markov Logic. In Proceedings of the Sixth IEEE International Conference on Data Mining (pp. 572-582), 2006. Hong Kong: IEEE Computer Society Press.

Singla, Parag and Kautz, Henry and Luo, Jiebo and Gallaher, Andrew (2008). Discovery of Social Relationships in Consumer Photo Collections using Markov Logic. In Proceedings of the CVPR Workshop on Semantic Learning and Applications in Multimedia, 2008. Anchorage, Alaska.

Song, Yang and Jiang, Jing and Zhao, Wayne Xin and Li, Sujian and Houfeng Wang (2012). Joint Learning for Coreference Resolution with Markov Logic. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2012). Jeju, Korea.

Sorower, Mohammad Shahed and Dietterich, Thomas G. and Doppa, Janardhan Rao and Orr, Walker and Tadepalli, Prasad and Fern, Xiaoli (2011). Inverting Grice’s Maxims to Learn Rules from Natural Language Extractions. In Advances in Neural Information Processing Systems 24 (NIPS-2011). Granada, Spain.

Tran, S. and Davis, L. (2008). Visual Event Modeling and Recognition using Markov Logic Networks. In Proceedings of the 10th European Conference on Computer Vision, 2008. Marseille, France.

Wu, Fei and Weld, Daniel S. (2008). Automatically Refining the Wikipedia Infobox Ontology. In Proceedings of the 17th International World Wide Web Conference, (WWW-08), Beijing, China, April, 2008.

Xia, Fei and Lewis, William and Poon, Hoifung (2009). Language ID in the Context of Harvesting Language Data off the Web. In Proceedings of the Conference of European Association for Computational Linguistics, 2009 (EACL-09). Athens, Greece: ACL.

Yoshikawa, Katsumasa and Riedel, Sebastian and Asahara, Masayuki and Matsumoto, Yuji (2009). Jointly Identifying Temporal Relations with Markov Logic. ACL 2009.