, Results for the predicate SameVenue in CORA Appendix C Clauses Learned by Discriminative Systems Clauses learned by discriminative systems
, -Author(a1,a2) Author(a3,a4), Title(a3,a5) SameBib(a1,a3) :-Title(a1,a2, Venue(a3,a4) SameBib(a3,a1) :-Title(a1,a2), Venue(a1,a5), Venue
, a1) :-Venue(a1,a2) SameAuthor(a1,a1) :-HasWordAuthor(a1,a2) SameAuthor(a2,a3) :-Author(a1,a2)
, Categorical data analysis, 2002.
, Relational Markov models and their application to adaptive web navigation, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, pp.143-152, 2002.
DOI : 10.1145/775047.775068
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.8783
, Learning Horn Expressions with LOGAN-H, J. Mach. Learn. Res, vol.8, pp.549-587, 2007.
DOI : 10.1016/s0890-5401(02)93162-7
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7745
, Discriminative Structure Learning of Markov Logic Networks, ILP '08: Proceedings of the 18th international conference on Inductive Logic Programming, pp.59-76, 2008.
DOI : 10.1007/978-3-540-85928-4_9
, Structure Learning of Markov Logic Networks through Iterated Local Search, Proceeding of the 2008 conference on ECAI 2008, pp.361-365, 2008.
, Joseph Bockhorst and Mark Craven Markov networks for detecting overlapping elements in sequence data, Neural Information Processing Systems 17 (NIPS, 2005.
, The use of the area under the ROC curve in the evaluation of machine learning algorithms, Pattern Recognition, vol.30, pp.1145-1159, 1997.
, Lifted first-order probabilistic inference, Proceedings of IJCAI-05, 19th International Joint Conference on Artificial Intelligence, pp.1319-1325, 2005.
, Bagging predictors, Machine Learning, pp.123-140, 1996.
DOI : 10.1007/BF00058655
, Facundo Bromberg, Alicia Carriquiry, Vasant Honavar, Giora Slutzki and Leigh Tesfatsion. Efficient Markov Network Structure Discovery using Independence Tests, SIAM International Conference on Data Mining, 2006.
, Jesse Davis and Mark Goadrich. The Relationship between Precision-Recall and ROC Curves, ICML '06: Proceedings of the 23rd international conference on Machine learning, pp.233-240, 2006.
, Luc De Raedt and Luc Dehaspe. Clausal Discovery, Machine Learning, pp.99-146, 1997.
, Probabilistic inductive logic programming -theory and applications, Lecture Notes in Computer Science, vol.4911, 2008.
, Maximum Likelihood from Incomplete Data via the EM Algorithm, Journal of the Royal Statistical Society. Series B (Methodological), vol.39, issue.1, pp.1-38, 1977.
, Discriminative Markov Logic Network Structure Learning Based on Propositionalization and ?? 2-Test, pp.24-35, 2010.
DOI : 10.1007/978-3-642-17316-5_3
URL : https://hal.archives-ouvertes.fr/hal-00512439
, Generative Structure Learning for Markov Logic Networks, Proceeding of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium, pp.63-75, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00504074
, Heuristic Method for Discriminative Structure Learning of Markov Logic Networks, 2010 Ninth International Conference on Machine Learning and Applications, pp.163-168, 2010.
DOI : 10.1109/ICMLA.2010.31
URL : https://hal.archives-ouvertes.fr/hal-00553007
, Apprentissage génératif de la structure de réseaux logiques de Markov à partir d'un graphe des prédicats, EGC, pp.413-424, 2011.
, Generative Structure Learning for Markov Logic Networks Based on Graph of Predicates, IJCAI, pp.1249-1254, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00584418
, Markov logic: A unifying framework for statistical relational learning, Introduction to Statistical Relational Learning, pp.339-371, 2007.
, Matthew Richardson and Parag Singla. Markov Logic, Probabilistic Inductive Logic Programming, pp.92-117, 2008.
, Uncertainty Reasoning for the Semantic Web I. chapitre Just Add Weights: Markov Logic for the Semantic Web, pp.1-25, 2008.
, An Empirical Evaluation of Bagging in Inductive Logic Programming, Proceedings of the Twelfth International Conference on Inductive Logic Programming, pp.48-65, 2002.
, Learning Probabilistic Relational Models, pp.1300-1309, 1999.
, Michael Genesereth and Nils Nilsson. Logical foundations of artificial intelligence, 1987.
, Lise Getoor and Ben Taskar. Introduction to statistical relational learning (adaptive computation and machine learning), 2007.
, Markov chain monte carlo in practice, 1999.
, Discriminative structure and parameter learning for Markov logic networks, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.416-423, 2008.
DOI : 10.1145/1390156.1390209
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.2326
, Max-Margin Weight Learning for Markov Logic Networks, ECML PKDD '09: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, pp.564-579, 2009.
, A general stochastic approach to solving problems with hard and soft constraints, 1996.
, Bayesian logic programming: Theory and tool, Introduction to Statistical Relational Learning, 2007.
, Counting belief propagation, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, UAI '09, pp.277-284, 2009.
, Structure Learning for Markov Logic Networks with Many Descriptive Attributes, Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010.
, Propositionalisation and Aggregates, Proceeding of the 5th PKDD, pp.277-288, 2001.
DOI : 10.1007/3-540-44794-6_23
, Learning the structure of Markov logic networks, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.441-448, 2005.
DOI : 10.1145/1102351.1102407
, Learning Markov logic network structure via hypergraph lifting, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, pp.505-512, 2009.
DOI : 10.1145/1553374.1553440
URL : http://ai.cs.washington.edu/www/media/papers/kok09a.pdf
, Learning Markov Logic Networks Using Structural Motifs, Proceedings of the 27th International Conference on Machine Learning (ICML-10), pp.551-558, 2010.
, The Alchemy system for statistical relational AI, 2009.
, Transformation-Based Learning Using Multirelational Aggregation, Proceedings of the 11th International Conference on Inductive Logic Programming, ILP '01, pp.142-155, 2001.
DOI : 10.1007/3-540-44797-0_12
, Comparative Evaluation of Approaches to Propositionalization, Proceedings of the 13th International Conference on Inductive Logic Programming, pp.194-217, 2003.
DOI : 10.1007/978-3-540-39917-9_14
, Ond?ej Ku?elka and Filip ?elezný HiFi: Tractable Propositionalization through Hierarchical Feature Construction, Filip ?elezný and Nada Lavra?, editeurs, Late Breaking Papers, the 18th International Conference on Inductive Logic Programming, 2008.
, Nada Lavrac and Saso Dzeroski Inductive logic programming: Techniques and applications, 1994.
, RSD: Relational Subgroup Discovery through First-Order Feature Construction, 12th International Conference on Inductive Logic Programming, pp.149-165, 2002.
DOI : 10.1007/3-540-36468-4_10
, Efficient Structure Learning of Markov Networks using L1-Regularization, Advances in Neural Information Processing Systems 19, pp.817-824, 2007.
, Julien Lesbegueries, Nicolas Lachiche and A Braud. A propositionalisation that preserves more continuous attribute domains, 2009.
, An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.584-591, 2008.
DOI : 10.1145/1390156.1390230
, On the limited memory BFGS method for large scale optimization, Mathematical Programming, pp.503-528, 1989.
DOI : 10.1007/BF01589116
, Daniel Lowd and Pedro Domingos Efficient Weight Learning for Markov Logic Networks, PKDD 2007: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases, pp.200-211, 2007.
, Handbook of biological statistics, 2009.
, Bottom-up learning of Markov logic network structure, Proceedings of the 24th international conference on Machine learning, ICML '07, pp.625-632, 2007.
DOI : 10.1145/1273496.1273575
, Lifted probabilistic inference with counting formulas, AAAI'08: Proceedings of the 23rd national conference on Artificial intelligence, pp.1062-1068, 2008.
, Stephen Muggleton and Cao Feng. Efficient Induction Of Logic Programs, New Generation Computing, 1990.
, Stephen Muggleton and C. Feng. Efficient Induction in Logic Programs, Stephen Muggleton, editeur, Inductive Logic Programming, pp.281-298, 1992.
, Dependency Networks for Relational Data, Fourth IEEE International Conference on Data Mining (ICDM'04), pp.170-177, 2004.
DOI : 10.1109/ICDM.2004.10101
, Numerical optimization, 1999.
DOI : 10.1007/b98874
, Hoifung Poon and Pedro Domingos. Sound and Efficient Inference with Probabilistic and Deterministic Dependencies, AAAI'06: Proceedings of the 21st national conference on Artificial intelligence, pp.458-463, 2006.
, Hoifung Poon and Pedro Domingos Joint unsupervised coreference resolution with Markov logic, Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP '08, pp.650-659, 2008.
, Hoifung Poon, Pedro Domingos and Marc Sumner. A general method for reducing the complexity of relational inference and its application to MCMC, Proceedings of the 23rd national conference on Artificial intelligence, pp.1075-1080, 2008.
, Learning logical definitions from relations, Machine Learning, vol.2, issue.3, pp.239-266, 1990.
DOI : 10.1007/BF00117105
, Readings in speech recognition, pp.267-296, 1990.
, Learning Relations by Pathfinding, Proc. of AAAI-92, pp.50-55, 1992.
, Automated Refinement of First-Order Horn-Clause Domain Theories, Machine Learning, pp.95-131, 1995.
, Markov Logic: A Unifying Framework for Statistical Relational Learning, Proceedings of the ICML-2004 Workshop on SRL and its Connections to Other Fields, pp.49-54, 2004.
, Fast incremental proximity search in large graphs, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.896-903, 2008.
DOI : 10.1145/1390156.1390269
, Taisuke Sato and Yoshitaka Kameya PRISM: A Language for Symbolic-statistical Modeling, Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI'97, pp.1330-1335, 1997.
, Shallow parsing with conditional random fields, Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology , NAACL '03, pp.134-141, 2003.
DOI : 10.3115/1073445.1073473
, Jude Shavlik and Sriraam Natarajan Speeding up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network, IJCAI'09: Proceedings of the 21st international jont conference on Artifical intelligence, pp.1951-1956, 2009.
, An Introduction to the Conjugate Gradient Method Without the Agonizing Pain, 1994.
, Relational clich??s: Constraining constructive induction during relational learning, ML, pp.203-207, 1991.
DOI : 10.1016/B978-1-55860-200-7.50044-1
, Parag Singla and Pedro Domingos Discriminative Training of Markov Logic Networks, Proc. of the Natl. Conf. on Artificial Intelligence, 2005.
, Parag Singla and Pedro Domingos. Lifted first-order belief propagation, Proceedings of the 23rd national conference on Artificial intelligence, pp.1094-1099, 2008.
, Peter Spirtes, Clark Glymour and Richard Scheines. Causation, prediction , and search, second edition (adaptive computation and machine learning), 2001.
, Discriminative Probabilistic Models for Relational Data, Proceedings of the 18th Annual Conference, 2002.