{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T20:32:30Z","timestamp":1774729950927,"version":"3.50.1"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319712482","type":"print"},{"value":"9783319712499","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-71249-9_13","type":"book-chapter","created":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T08:53:43Z","timestamp":1514537623000},"page":"203-219","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks"],"prefix":"10.1007","author":[{"given":"Nicola","family":"Di Mauro","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio","family":"Vergari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Teresa M. A.","family":"Basile","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Floriana","family":"Esposito","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,12,30]]},"reference":[{"key":"13_CR1","unstructured":"Bekker, J., Davis, J., Choi, A., Darwiche, A., Van den Broeck, G.: Tractable learning for complex probability queries. In: NIPS (2015)"},{"key":"13_CR2","unstructured":"Boutilier, C., Friedman, N., Goldszmidt, M., Koller, D.: Context-specific independence in Bayesian networks. In: UAI (1996)"},{"key":"13_CR3","volume-title":"The Winmine Toolkit","author":"M Chickering","year":"2002","unstructured":"Chickering, M.: The Winmine Toolkit. Microsoft, Redmond (2002)"},{"key":"13_CR4","unstructured":"Choi, A., Van den Broeck, G., Darwiche, A.: Tractable learning for structured probability spaces: a case study in learning preference distributions. In: IJCAI (2015)"},{"key":"13_CR5","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1109\/TIT.1968.1054142","volume":"14","author":"C Chow","year":"1968","unstructured":"Chow, C., Liu, C.: Approximating discrete probability distributions with dependence trees. IEEE Trans. Inf. Theory 14, 462\u2013467 (1968)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"13_CR6","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1145\/765568.765570","volume":"50","author":"A Darwiche","year":"2003","unstructured":"Darwiche, A.: A differential approach to inference in Bayesian networks. JACM 50, 280\u2013305 (2003)","journal-title":"JACM"},{"key":"13_CR7","unstructured":"Di Mauro, N., Vergari, A., Esposito, F.: Multi-label classification with cutset networks. In: PGM (2016)"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Di Mauro, N., Vergari, A., Basile, T.: Learning Bayesian random cutset forests. In: ISMIS (2015)","DOI":"10.1007\/978-3-319-25252-0_13"},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Di Mauro, N., Vergari, A., Esposito, F.: Learning accurate cutset networks by exploiting decomposability. In: AIXIA (2015)","DOI":"10.1007\/978-3-319-24309-2_17"},{"key":"13_CR10","first-page":"3","volume":"63","author":"P Geurts","year":"2006","unstructured":"Geurts, P., Ernst, D., Wehenkel, L.: Extremely randomized trees. MLJ 63, 3\u201342 (2006)","journal-title":"MLJ"},{"key":"13_CR11","unstructured":"Haaren, J.V., Davis, J.: Markov network structure learning: a randomized feature generation approach. In: AAAI (2012)"},{"key":"13_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning","author":"T Hastie","year":"2009","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-0-387-21606-5"},{"key":"13_CR13","volume-title":"Probabilistic Graphical Models: Principles and Techniques","author":"D Koller","year":"2009","unstructured":"Koller, D., Friedman, N.: Probabilistic Graphical Models: Principles and Techniques. MIT Press, Cambridge (2009)"},{"key":"13_CR14","unstructured":"Larochelle, H., Murray, I.: The neural autoregressive distribution estimator. In: AISTATS (2011)"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Lowd, D., Davis, J.: Learning Markov network structure with decision trees. In: ICDM (2010)","DOI":"10.1109\/ICDM.2010.128"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Lowd, D., Domingos, P.: Naive Bayes models for probability estimation. In: ICML (2005)","DOI":"10.1145\/1102351.1102418"},{"key":"13_CR17","unstructured":"Lowd, D., Rooshenas, A.: Learning Markov networks with arithmetic circuits. In: AISTATS (2013)"},{"key":"13_CR18","first-page":"1","volume":"1","author":"M Meil","year":"2000","unstructured":"Meil, M., Jordan, M.I.: Learning with mixtures of trees. JMLR 1, 1\u201348 (2000)","journal-title":"JMLR"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Poon, H., Domingos, P.: Sum-product network: a new deep architecture. In: NIPS Workshop on Deep Learning and Unsupervised Feature Learning (2011)","DOI":"10.1109\/ICCVW.2011.6130310"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Rahman, T., Gogate, V.: Learning ensembles of cutset networks. In: AAAI (2016)","DOI":"10.1609\/aaai.v30i1.10428"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Rahman, T., Kothalkar, P., Gogate, V.: Cutset networks: a simple, tractable, and scalable approach for improving the accuracy of Chow-Liu trees. In: ECML\/PKDD (2014)","DOI":"10.1007\/978-3-662-44851-9_40"},{"key":"13_CR22","unstructured":"Rooshenas, A., Lowd, D.: Learning sum-product networks with direct and indirect variable interactions. In: ICML, pp. 710\u2013718 (2014)"},{"key":"13_CR23","first-page":"273","volume":"82","author":"D Roth","year":"1996","unstructured":"Roth, D.: On the hardness of approximate reasoning. AI 82, 273\u2013302 (1996)","journal-title":"AI"},{"key":"13_CR24","unstructured":"Scanagatta, M., Corani, G., de Campos, C.P., Zaffalon, M.: Learning treewidth-bounded Bayesian networks with thousands of variables. In: NIPS (2016)"},{"key":"13_CR25","unstructured":"Theis, L., van den Oord, A., Bethge, M.: A note on the evaluation of generative models. In: ICLR (2016)"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Vergari, A., Di Mauro, N., Esposito, F.: Simplifying, regularizing and strengthening sum-product network structure learning. In: ECML\/PKDD (2015)","DOI":"10.1007\/978-3-319-23525-7_21"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-71249-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,29]],"date-time":"2022-12-29T01:25:39Z","timestamp":1672277139000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-71249-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319712482","9783319712499"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-71249-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"30 December 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Skopje","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macedonia","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":"18 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ecmlpkdd2017.ijs.si\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}