{"id":"https://openalex.org/W3103613142","doi":"https://doi.org/10.1109/tkde.2020.3038799","title":"Improving Deep Forest by Screening","display_name":"Improving Deep Forest by Screening","publication_year":2020,"publication_date":"2020-11-17","ids":{"openalex":"https://openalex.org/W3103613142","doi":"https://doi.org/10.1109/tkde.2020.3038799","mag":"3103613142"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2020.3038799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3038799","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102011859","display_name":"Ming Pang","orcid":"https://orcid.org/0000-0003-0454-0808"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Pang","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001601850","display_name":"Kai Ming Ting","orcid":"https://orcid.org/0000-0001-7892-6194"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Ming Ting","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040157899","display_name":"Peng Zhao","orcid":"https://orcid.org/0000-0001-7925-8255"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhao","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100621138","display_name":"Zhi\u2010Hua Zhou","orcid":"https://orcid.org/0000-0003-0746-1494"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi-Hua Zhou","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102011859"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":1.7233,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.87919067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"34","issue":"9","first_page":"4298","last_page":"4312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9995999932289124,"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/T10320","display_name":"Neural Networks and Applications","score":0.9995999932289124,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9990000128746033,"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/T10057","display_name":"Face and Expression Recognition","score":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8522172570228577},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7891973853111267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7709957361221313},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.7665067315101624},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5914559364318848},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5876544713973999},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5866364240646362},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.5254111289978027},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4938279092311859},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4137466251850128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3431718945503235},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13564881682395935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07580816745758057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8522172570228577},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7891973853111267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7709957361221313},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.7665067315101624},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5914559364318848},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5876544713973999},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5866364240646362},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.5254111289978027},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4938279092311859},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4137466251850128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3431718945503235},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13564881682395935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07580816745758057},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2020.3038799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3038799","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.7099999785423279,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G528746023","display_name":null,"funder_award_id":"61921006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G697213553","display_name":null,"funder_award_id":"61751306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324852","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1612277053","https://openalex.org/W1645816215","https://openalex.org/W2009985472","https://openalex.org/W2028560166","https://openalex.org/W2056132907","https://openalex.org/W2063978378","https://openalex.org/W2070996757","https://openalex.org/W2100600375","https://openalex.org/W2108949035","https://openalex.org/W2110119381","https://openalex.org/W2111072639","https://openalex.org/W2112796928","https://openalex.org/W2115755118","https://openalex.org/W2127831831","https://openalex.org/W2128466927","https://openalex.org/W2149363887","https://openalex.org/W2152705230","https://openalex.org/W2160815625","https://openalex.org/W2164598857","https://openalex.org/W2171896402","https://openalex.org/W2266560361","https://openalex.org/W2313501142","https://openalex.org/W2579923771","https://openalex.org/W2592340788","https://openalex.org/W2605213558","https://openalex.org/W2781712876","https://openalex.org/W2782963495","https://openalex.org/W2787894218","https://openalex.org/W2907066344","https://openalex.org/W2912573428","https://openalex.org/W2913407066","https://openalex.org/W2920267415","https://openalex.org/W2920882913","https://openalex.org/W2952921651","https://openalex.org/W2955354980","https://openalex.org/W2963862530","https://openalex.org/W2964152520","https://openalex.org/W2972156159","https://openalex.org/W2986119938","https://openalex.org/W2995843219","https://openalex.org/W3054552769","https://openalex.org/W3088563745","https://openalex.org/W3100535899","https://openalex.org/W3106968132","https://openalex.org/W3118608800","https://openalex.org/W4232478844","https://openalex.org/W4232714830","https://openalex.org/W4240294902","https://openalex.org/W4289236186","https://openalex.org/W6676984168","https://openalex.org/W6678635528","https://openalex.org/W6680922791","https://openalex.org/W6683033130","https://openalex.org/W6684191040","https://openalex.org/W6685961532","https://openalex.org/W6697609866","https://openalex.org/W6732517885","https://openalex.org/W6739190457","https://openalex.org/W6767325278","https://openalex.org/W6770659305","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295","https://openalex.org/W2804482613","https://openalex.org/W4232714830"],"abstract_inverted_index":{"Most":[0],"studies":[1],"about":[2],"deep":[3,29,42,47,81,172],"learning":[4,30,79,130],"are":[5,19,119,127],"based":[6],"on":[7,60],"neural":[8],"network":[9],"models,":[10],"where":[11],"many":[12,116],"layers":[13],"of":[14,80,89,168,196],"parameterized":[15],"nonlinear":[16],"differentiable":[17],"modules":[18,37],"trained":[20],"by":[21,35,191],"backpropagation.":[22],"Recently,":[23],"it":[24,84],"has":[25,49,56],"been":[26],"shown":[27],"that":[28,46,91,176],"can":[31],"also":[32],"be":[33,94],"realized":[34],"non-differentiable":[36],"without":[38],"backpropagation":[39],"training":[40],"called":[41],"forest.":[43,82,173],"We":[44],"identify":[45],"forest":[48],"high":[50,100,164],"time":[51,186],"costs":[52],"and":[53,70,122,188],"memory":[54,189],"requirements\u2014this":[55],"inhibited":[57],"its":[58],"use":[59],"large-scale":[61],"datasets.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66],"propose":[67],"a":[68],"simple":[69],"effective":[71],"approach":[72,155,178],"with":[73,184],"three":[74],"main":[75],"strategies":[76],"for":[77,108,129],"efficient":[78],"First,":[83],"substantially":[85],"reduces":[86],"the":[87,105,112,124,144,153,158,166],"number":[88,167],"instances":[90,98],"needs":[92],"to":[93,104,142,163,193],"processed":[95],"through":[96],"redirecting":[97],"having":[99],"predictive":[101,182],"confidence":[102],"straight":[103],"final":[106],"level":[107],"prediction,":[109],"by-passing":[110],"all":[111],"intermediate":[113],"levels.":[114],"Second,":[115],"non-informative":[117],"features":[118],"screened":[120],"out,":[121],"only":[123],"informative":[125],"ones":[126],"used":[128],"at":[131],"each":[132],"level.":[133],"Third,":[134],"an":[135],"unsupervised":[136],"feature":[137],"transformation":[138],"procedure":[139],"is":[140],"proposed":[141,154],"replace":[143],"supervised":[145],"multi-grained":[146],"scanning":[147],"procedure.":[148],"Our":[149],"theoretical":[150],"analysis":[151],"supports":[152],"in":[156,171],"varying":[157],"model":[159],"complexity":[160],"from":[161],"low":[162],"as":[165],"levels":[169],"increases":[170],"Experiments":[174],"show":[175],"our":[177],"achieves":[179],"highly":[180],"competitive":[181],"performance":[183],"reduced":[185],"cost":[187],"requirement":[190],"one":[192],"two":[194],"orders":[195],"magnitude.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
