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Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases.

, , , and . Mach. Learn., 100 (1): 75-100 (2015)

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Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text, , , , , and . Statistical Relational Artificial Intelligence, Papers from the 2013 AAAI Workshop, Bellevue, Washington, USA, July 15, 2013, volume WS-13-16 of AAAI Workshops, AAAI, (2013)Effectively creating weakly labeled training examples via approximate domain knowledge, , , , , and . Inductive Logic Programming, Springer, (2015)Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, , , and . Synthesis Lectures on Artificial Intelligence and Machine Learning Morgan & Claypool Publishers, (2016)Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models, , , , , , and . Proceedings of ECML, (2010)Graph Enhanced Memory Networks for Sentiment Analysis., , and . ECML/PKDD (1), volume 10534 of Lecture Notes in Computer Science, page 374-389. Springer, (2017)Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks, , and . (2019)cite arxiv:1907.06732Comment: 12 Pages, 6 Figures.Equitable Partitions of Concave Free Energies., and . UAI, page 602-611. AUAI Press, (2015)Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models., , , and . Pacific Symposium on Biocomputing, page 192-203. (2003)Structured Object-Aware Physics Prediction for Video Modeling and Planning., , , , and . ICLR, OpenReview.net, (2020)Statistical Relational Learning., and . Encyclopedia of Machine Learning and Data Mining, Springer, (2017)