{"id":"https://openalex.org/W2979775090","doi":"https://doi.org/10.1007/s11263-019-01237-6","title":"End-to-End Learning of Decision Trees and Forests","display_name":"End-to-End Learning of Decision Trees and Forests","publication_year":2019,"publication_date":"2019-10-09","ids":{"openalex":"https://openalex.org/W2979775090","doi":"https://doi.org/10.1007/s11263-019-01237-6","mag":"2979775090"},"language":"en","primary_location":{"id":"doi:10.1007/s11263-019-01237-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-019-01237-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-019-01237-6.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11263-019-01237-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028968900","display_name":"Thomas M. Hehn","orcid":"https://orcid.org/0000-0002-4062-6222"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Thomas M. Hehn","raw_affiliation_strings":["Intelligent Vehicles Group, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Intelligent Vehicles Group, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074902093","display_name":"Julian F. P. Kooij","orcid":"https://orcid.org/0000-0001-9919-0710"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Julian F. P. Kooij","raw_affiliation_strings":["Intelligent Vehicles Group, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Intelligent Vehicles Group, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020048224","display_name":"Fred A. Hamprecht","orcid":"https://orcid.org/0000-0003-4148-5043"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fred A. Hamprecht","raw_affiliation_strings":["HCI/IWR, Heidelberg University, 69120, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"HCI/IWR, Heidelberg University, 69120, Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028968900"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":{"value":2890,"currency":"EUR","value_usd":3690},"apc_paid":{"value":2890,"currency":"EUR","value_usd":3690},"fwci":4.0454,"has_fulltext":true,"cited_by_count":62,"citation_normalized_percentile":{"value":0.95168201,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"128","issue":"4","first_page":"997","last_page":"1011"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9218394756317139},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.7702153921127319},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6958576440811157},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6619772911071777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5963746309280396},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5309253334999084},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4803420305252075},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.4801085293292999},{"id":"https://openalex.org/keywords/incremental-decision-tree","display_name":"Incremental decision tree","score":0.4497874677181244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34915491938591003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27738237380981445},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2220403254032135}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9218394756317139},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7702153921127319},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6958576440811157},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6619772911071777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5963746309280396},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5309253334999084},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4803420305252075},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.4801085293292999},{"id":"https://openalex.org/C10229987","wikidata":"https://www.wikidata.org/wiki/Q17083028","display_name":"Incremental decision tree","level":4,"score":0.4497874677181244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34915491938591003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27738237380981445},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2220403254032135}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11263-019-01237-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-019-01237-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-019-01237-6.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},{"id":"pmh:tud:oai:tudelft.nl:uuid:b8b380f9-c5ac-4112-9206-d39bb60f9483","is_oa":true,"landing_page_url":"http://resolver.tudelft.nl/uuid:b8b380f9-c5ac-4112-9206-d39bb60f9483","pdf_url":"http://resolver.tudelft.nl/uuid:b8b380f9-c5ac-4112-9206-d39bb60f9483","source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Computer Vision, 128 (2020)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s11263-019-01237-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-019-01237-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-019-01237-6.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G2649974504","display_name":null,"funder_award_id":"HA 4364/10-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2979775090.pdf","grobid_xml":"https://content.openalex.org/works/W2979775090.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W13188192","https://openalex.org/W137456267","https://openalex.org/W148877464","https://openalex.org/W182586680","https://openalex.org/W1585367646","https://openalex.org/W1599308405","https://openalex.org/W1953644808","https://openalex.org/W1969013163","https://openalex.org/W1970074386","https://openalex.org/W1990420052","https://openalex.org/W1992808738","https://openalex.org/W2021404082","https://openalex.org/W2025653905","https://openalex.org/W2025887562","https://openalex.org/W2032771218","https://openalex.org/W2059424674","https://openalex.org/W2075450508","https://openalex.org/W2081136789","https://openalex.org/W2100659887","https://openalex.org/W2104266970","https://openalex.org/W2106525823","https://openalex.org/W2107285841","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2123199310","https://openalex.org/W2125055259","https://openalex.org/W2125556102","https://openalex.org/W2131296063","https://openalex.org/W2135931458","https://openalex.org/W2142859438","https://openalex.org/W2143353778","https://openalex.org/W2148423395","https://openalex.org/W2149706766","https://openalex.org/W2157017541","https://openalex.org/W2164598857","https://openalex.org/W2172156083","https://openalex.org/W2179503016","https://openalex.org/W2220384803","https://openalex.org/W2290283816","https://openalex.org/W2294581849","https://openalex.org/W2330820318","https://openalex.org/W2340897893","https://openalex.org/W2499439150","https://openalex.org/W2592790041","https://openalex.org/W2604231779","https://openalex.org/W2613547692","https://openalex.org/W2622755869","https://openalex.org/W2748261474","https://openalex.org/W2750384547","https://openalex.org/W2767421475","https://openalex.org/W2769421449","https://openalex.org/W2899771611","https://openalex.org/W2899835905","https://openalex.org/W2911964244","https://openalex.org/W2949427550","https://openalex.org/W2949683077","https://openalex.org/W2952122856","https://openalex.org/W2963393494","https://openalex.org/W2963438370","https://openalex.org/W2964121744","https://openalex.org/W3085162807","https://openalex.org/W3120740533","https://openalex.org/W4247777826","https://openalex.org/W4297073864","https://openalex.org/W6631190155","https://openalex.org/W6746418821","https://openalex.org/W6756040250","https://openalex.org/W6817491142","https://openalex.org/W6843735874"],"related_works":["https://openalex.org/W1982169401","https://openalex.org/W2030894524","https://openalex.org/W2591672004","https://openalex.org/W4319437832","https://openalex.org/W1648970942","https://openalex.org/W4243803609","https://openalex.org/W4387869645","https://openalex.org/W4293151273","https://openalex.org/W2348694184","https://openalex.org/W2356463514"],"abstract_inverted_index":{"Abstract":[0],"Conventional":[1],"decision":[2,64,90,93,149],"trees":[3,91,105,150],"have":[4,49],"a":[5,11,28,59,74,97],"number":[6],"of":[7,40,57,63,77,128],"favorable":[8],"properties,":[9],"including":[10],"small":[12,75],"computational":[13],"footprint,":[14],"interpretability,":[15],"and":[16,92,100,131,133,151,172],"the":[17,35,55,66,104,126],"ability":[18],"to":[19,96,143],"learn":[20,163],"from":[21],"little":[22],"training":[23,102],"data.":[24],"However,":[25],"they":[26],"lack":[27],"key":[29],"quality":[30],"that":[31,39,68,135,159],"has":[32],"helped":[33],"fuel":[34],"deep":[36],"learning":[37,86,145],"revolution:":[38],"being":[41],"end-to-end":[42,85],"trainable.":[43],"Kontschieder":[44],"et":[45],"al.":[46],"(ICCV,":[47],"2015)":[48],"addressed":[50],"this":[51],"deficit,":[52],"but":[53,112],"at":[54,109,119],"cost":[56],"losing":[58],"main":[60],"attractive":[61],"trait":[62],"trees:":[65],"fact":[67],"each":[69],"sample":[70],"is":[71],"routed":[72],"along":[73],"subset":[76],"tree":[78],"nodes":[79],"only.":[80],"We":[81,153],"here":[82],"present":[83],"an":[84,114],"scheme":[87],"for":[88,147],"deterministic":[89,118],"forests.":[94,152],"Thanks":[95],"new":[98],"model":[99],"expectation\u2013maximization":[101],"scheme,":[103],"are":[106],"fully":[107],"probabilistic":[108],"train":[110],"time,":[111],"after":[113],"annealing":[115,129],"process":[116],"become":[117],"test":[120],"time.":[121],"In":[122],"experiments":[123],"we":[124],"explore":[125],"effect":[127],"visually":[130],"quantitatively,":[132],"find":[134],"our":[136,160],"method":[137],"performs":[138],"on":[139,156],"par":[140],"or":[141],"superior":[142],"standard":[144],"algorithms":[146],"oblique":[148,170],"further":[154],"demonstrate":[155],"image":[157],"datasets":[158],"approach":[161],"can":[162],"more":[164],"complex":[165],"split":[166],"functions":[167],"than":[168],"common":[169],"ones,":[171],"facilitates":[173],"interpretability":[174],"through":[175],"spatial":[176],"regularization.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":6}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}