{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T12:07:04Z","timestamp":1783685224575,"version":"3.55.0"},"publisher-location":"Cham","reference-count":43,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319780894","type":"print"},{"value":"9783319780900","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-78090-0_7","type":"book-chapter","created":{"date-parts":[[2018,3,14]],"date-time":"2018-03-14T13:04:58Z","timestamp":1521032698000},"page":"94-111","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach"],"prefix":"10.1007","author":[{"given":"Navdeep","family":"Kaur","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9297-2071","authenticated-orcid":false,"given":"Gautam","family":"Kunapuli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tushar","family":"Khot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2873-9152","authenticated-orcid":false,"given":"Kristian","family":"Kersting","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Cohen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9889-6260","authenticated-orcid":false,"given":"Sriraam","family":"Natarajan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,3,15]]},"reference":[{"issue":"1","key":"7_CR1","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1207\/s15516709cog0901_7","volume":"9","author":"DH Ackley","year":"1985","unstructured":"Ackley, D.H., Hinton, G.E., Sejnowski, T.J.: A learning algorithm for Boltzmann machines. Cogn. Sci. 9(1), 147\u2013169 (1985)","journal-title":"Cogn. Sci."},{"key":"7_CR2","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra, J., Bengio, Y.: Random search for hyper-parameter optimization. JMLR 13, 281\u2013305 (2012)","journal-title":"JMLR"},{"key":"7_CR3","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. JMLR 3, 993\u20131022 (2003)","journal-title":"JMLR"},{"key":"7_CR4","unstructured":"Blockeel, H., Uwents, W.: Using neural networks for relational learning. In: ICML 2004 Workshop on SRL, pp. 23\u201328 (2004)"},{"key":"7_CR5","doi-asserted-by":"crossref","unstructured":"Carlson, A., Betteridge, J., Kisiel, B., Settles, B., Hruschka Jr., E.R., Mitchell, T.M.: Toward an architecture for never-ending language learning. In: AAAI, pp. 1306\u20131313 (2010)","DOI":"10.1609\/aaai.v24i1.7519"},{"key":"7_CR6","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511801389","volume-title":"An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods","author":"N Cristianini","year":"2000","unstructured":"Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge University Press, New York (2000)"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Das, M., Wu, Y., Khot, T., Kersting, K., Natarajan, S.: Scaling lifted probabilistic inference and learning via graph databases. In: SDM (2016)","DOI":"10.1137\/1.9781611974348.83"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Davis, J., Goadrich, M.: The relationship between Precision-Recall and ROC curves. In: ICML (2006)","DOI":"10.1145\/1143844.1143874"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"De Raedt, L., Kersting, K., Natarajan, S., Poole, D. (eds.): Statistical Relational Artificial Intelligence: Logic, Probability, and Computation. Morgan and Claypool Publishers, San Rafael (2016)","DOI":"10.2200\/S00692ED1V01Y201601AIM032"},{"key":"7_CR10","unstructured":"Deng, L.: Connecting deep learning features to log-linear models. In: Log-Linear Models, Extensions and Applications. MIT Press (2015)"},{"key":"7_CR11","first-page":"145","volume":"9","author":"G Desjardins","year":"2010","unstructured":"Desjardins, G., Courville, A., Bengio, Y., Vincent, P., Dellaleau, O.: Parallel tempering for training of restricted Boltzmann machines. AISTATS 9, 145\u2013152 (2010)","journal-title":"AISTATS"},{"key":"7_CR12","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-01549-6","volume-title":"Markov Logic: An Interface Layer for AI","author":"P Domingos","year":"2009","unstructured":"Domingos, P., Lowd, D.: Markov Logic: An Interface Layer for AI. Morgan & Claypool Publishers, San Rafael (2009)"},{"issue":"1","key":"7_CR13","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s10994-013-5392-1","volume":"94","author":"MVM Fran\u00e7a","year":"2014","unstructured":"Fran\u00e7a, M.V.M., Zaverucha, G., d\u2019Avila Garcez, A.S.: Fast relational learning using bottom clause propositionalization with artificial neural networks. Mach. Learn. 94(1), 81\u2013104 (2014)","journal-title":"Mach. Learn."},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Gehler, P.V., Holub, A.D., Welling, M.: The rate adapting Poisson model for information retrieval and object recognition. In: ICML, pp. 337\u2013344 (2006)","DOI":"10.1145\/1143844.1143887"},{"key":"7_CR15","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/7432.001.0001","volume-title":"Introduction to Statistical Relational Learning","author":"L Getoor","year":"2007","unstructured":"Getoor, L., Taskar, B.: Introduction to Statistical Relational Learning. MIT Press, Cambridge (2007)"},{"key":"7_CR16","volume-title":"Deep Learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)"},{"key":"7_CR17","doi-asserted-by":"publisher","first-page":"1771","DOI":"10.1162\/089976602760128018","volume":"14","author":"GE Hinton","year":"2002","unstructured":"Hinton, G.E.: Training products of experts by minimizing contrastive divergence. Neural Comput. 14, 1771\u20131800 (2002)","journal-title":"Neural Comput."},{"key":"7_CR18","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S.: A fast learning algorithm for deep belief nets. Neural Comput. 18, 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Hinton, G.E.: To recognize shapes first learn to generate images. In: Computational Neuroscience: Theoretical Insights into Brain Function. Elsevier (2007)","DOI":"10.1016\/S0079-6123(06)65034-6"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Hu, Z., Ma, X., Liu, Z., Hovy, E.H., Xing, E.P.: Harnessing deep neural networks with logic rules. In: ACL (2016)","DOI":"10.18653\/v1\/P16-1228"},{"key":"7_CR21","unstructured":"Kazemi, S., Buchman, D., Kersting, K., Natarajan, S., Poole, D.: Relational logistic regression. In: KR (2014)"},{"key":"7_CR22","doi-asserted-by":"crossref","unstructured":"Khot, T., Natarajan, S., Kersting, K., Shavlik, J.: Learning Markov logic networks via functional gradient boosting. In: ICDM (2011)","DOI":"10.1109\/ICDM.2011.87"},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Kok, S., Domingos, P.: Learning Markov logic network structure via hypergraph lifting. In: ICML (2009)","DOI":"10.1145\/1553374.1553440"},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Kok, S., Domingos, P.: Learning Markov logic networks using structural motifs. In: ICML (2010)","DOI":"10.1145\/1553374.1553440"},{"key":"7_CR25","unstructured":"Kok, S., Sumner, M., Richardson, M., et al.: The Alchemy system for statistical relational AI. University of Washington, Technical report (2010)"},{"key":"7_CR26","volume-title":"Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning","author":"D Koller","year":"2009","unstructured":"Koller, D., Friedman, N.: Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning. The MIT Press, Cambridge (2009)"},{"key":"7_CR27","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s10994-009-5163-1","volume":"78","author":"N Landwehr","year":"2010","unstructured":"Landwehr, N., Passerini, A., De Raedt, L., Frasconi, P.: Fast learning of relational Kernels. Mach. Learn. 78, 305\u2013342 (2010)","journal-title":"Mach. Learn."},{"issue":"1","key":"7_CR28","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s10994-010-5205-8","volume":"81","author":"N Lao","year":"2010","unstructured":"Lao, N., Cohen, W.: Relational retrieval using a combination of path-constrained random walks. J. Mach. Learn. 81(1), 53\u201367 (2010)","journal-title":"J. Mach. Learn."},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"Larochelle, H., Bengio, Y.: Classification using discriminative restricted Boltzmann machines. In: ICML, pp. 536\u2013543 (2008)","DOI":"10.1145\/1390156.1390224"},{"key":"7_CR30","doi-asserted-by":"crossref","unstructured":"Lecun, Y., Chopra, S., Hadsell, R., Marc\u2019Aurelio, R., Huang, F.: A tutorial on energy-based learning. In: Predicting Structured Data. MIT Press (2006)","DOI":"10.7551\/mitpress\/7443.003.0014"},{"key":"7_CR31","doi-asserted-by":"crossref","unstructured":"Mihalkova, L., Mooney, R.: Bottom-up learning of Markov logic network structure. In: ICML (2007)","DOI":"10.1145\/1273496.1273575"},{"issue":"1","key":"7_CR32","first-page":"25","volume":"86","author":"S Natarajan","year":"2012","unstructured":"Natarajan, S., Khot, T., Kersting, K., Guttmann, B., Shavlik, J.: Gradient-based boosting for statistical relational learning: the relational dependency network case. MLJ 86(1), 25\u201356 (2012)","journal-title":"MLJ"},{"key":"7_CR33","series-title":"SpringerBriefs in Computer Science","volume-title":"Boosted Statistical Relational Learners. From Benchmarks to Data-Driven Medicine","year":"2016","unstructured":"Natarajan, S., Khot, T., Kersting, K., Shavlik, J. (eds.): Boosted Statistical Relational Learners. From Benchmarks to Data-Driven Medicine. SpringerBriefs in Computer Science. Springer, New York (2016)"},{"issue":"1\u20133","key":"7_CR34","first-page":"223","volume":"54","author":"S Natarajan","year":"2008","unstructured":"Natarajan, S., Tadepalli, P., Dietterich, T., Fern, A.: Learning first-order probabilistic models with combining rules. AMAI 54(1\u20133), 223\u2013256 (2008)","journal-title":"AMAI"},{"key":"7_CR35","unstructured":"Poon, H., Domingos, P.: Joint inference in information extraction. In: AAAI (2007)"},{"key":"7_CR36","volume-title":"C4.5: Programs for Machine Learning","author":"J Quinlan","year":"1993","unstructured":"Quinlan, J.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers Inc., San Mateo (1993)"},{"key":"7_CR37","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s10994-006-5833-1","volume":"62","author":"M Richardson","year":"2006","unstructured":"Richardson, M., Domingos, P.: Markov logic networks. Mach. Learn. 62, 107\u2013136 (2006)","journal-title":"Mach. Learn."},{"issue":"3\u20134","key":"7_CR38","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1007\/BF03037227","volume":"13","author":"S Muggleton","year":"1995","unstructured":"Muggleton, S.: Inverse entailment and Progol. New Gener. Comput. 13(3\u20134), 245\u2013286 (1995)","journal-title":"New Gener. Comput."},{"key":"7_CR39","doi-asserted-by":"crossref","unstructured":"Salakhutdinov, R., Mnih, A., Hinton, G.: Restricted Boltzmann machines for collaborative filtering. In: ICML, pp. 791\u2013798 (2007)","DOI":"10.1145\/1273496.1273596"},{"key":"7_CR40","unstructured":"Snoek, J., Larochelle, H., Adams, R.P.: Practical Bayesian optimization of machine learning algorithms. In: NIPS, pp. 2951\u20132959 (2012)"},{"key":"7_CR41","doi-asserted-by":"crossref","unstructured":"Taylor, G.W., Hinton, G.E., Roweis, S.T.: Modeling human motion using binary latent variables. In: NIPS (2007)","DOI":"10.7551\/mitpress\/7503.003.0173"},{"key":"7_CR42","doi-asserted-by":"crossref","unstructured":"Tieleman, T.: Training restricted Boltzmann machines using approximations to the likelihood gradient. In: ICML, pp. 1064\u20131071 (2008)","DOI":"10.1145\/1390156.1390290"},{"key":"7_CR43","unstructured":"Wang, W., Cohen, W.: Learning first-order logic embeddings via matrix factorization. In: IJCAI (2016)"}],"container-title":["Lecture Notes in Computer Science","Inductive Logic Programming"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-78090-0_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T16:10:43Z","timestamp":1693584643000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-78090-0_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319780894","9783319780900"],"references-count":43,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-78090-0_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"ILP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Inductive Logic Programming","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Orl\u00e9ans","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ilp2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ilp2017.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}