{"id":"https://openalex.org/W2963156835","doi":"https://doi.org/10.24963/ijcai.2018/700","title":"Building Sparse Deep Feedforward Networks using Tree Receptive Fields","display_name":"Building Sparse Deep Feedforward Networks using Tree Receptive Fields","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2963156835","doi":"https://doi.org/10.24963/ijcai.2018/700","mag":"2963156835"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/700","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/700","pdf_url":"https://www.ijcai.org/proceedings/2018/0700.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0700.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100761511","display_name":"Xiaopeng Li","orcid":"https://orcid.org/0000-0001-7686-0283"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaopeng Li","raw_affiliation_strings":["Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018500051","display_name":"Zhourong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhourong Chen","raw_affiliation_strings":["Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070840566","display_name":"Nevin L. Zhang","orcid":"https://orcid.org/0000-0002-4662-3217"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Nevin L. Zhang","raw_affiliation_strings":["Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070840566"],"corresponding_institution_ids":["https://openalex.org/I200769079"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23623841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5045","last_page":"5051"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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":0.9986000061035156,"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/T10320","display_name":"Neural Networks and Applications","score":0.9980000257492065,"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/computer-science","display_name":"Computer science","score":0.7384316921234131},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6678966879844666},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.6144450306892395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6083768606185913},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5724814534187317},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.5689187049865723},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5593974590301514},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5356006622314453},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5302308201789856},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4899510443210602},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4537515938282013},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43989092111587524},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.43360599875450134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3823840022087097},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21268042922019958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7384316921234131},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6678966879844666},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.6144450306892395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6083768606185913},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5724814534187317},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.5689187049865723},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5593974590301514},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5356006622314453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5302308201789856},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4899510443210602},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4537515938282013},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43989092111587524},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.43360599875450134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3823840022087097},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21268042922019958},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2018/700","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/700","pdf_url":"https://www.ijcai.org/proceedings/2018/0700.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-94429","is_oa":false,"landing_page_url":"http://www.scopus.com/record/display.url?eid=2-s2.0-85055708778&origin=inward","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/700","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/700","pdf_url":"https://www.ijcai.org/proceedings/2018/0700.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963156835.pdf","grobid_xml":"https://content.openalex.org/works/W2963156835.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1614298861","https://openalex.org/W1665214252","https://openalex.org/W1983041433","https://openalex.org/W2002847526","https://openalex.org/W2025768430","https://openalex.org/W2095705004","https://openalex.org/W2109779438","https://openalex.org/W2117941247","https://openalex.org/W2125389748","https://openalex.org/W2142544077","https://openalex.org/W2163166770","https://openalex.org/W2170240176","https://openalex.org/W2521957343","https://openalex.org/W2553303224","https://openalex.org/W2611669764","https://openalex.org/W2952278564","https://openalex.org/W2962965870","https://openalex.org/W2963000224","https://openalex.org/W2963454111","https://openalex.org/W2963981420","https://openalex.org/W2964217848","https://openalex.org/W4293406386","https://openalex.org/W4294170691","https://openalex.org/W4295185264","https://openalex.org/W4295225525"],"related_works":["https://openalex.org/W2089544495","https://openalex.org/W2079003682","https://openalex.org/W1555021777","https://openalex.org/W2115072676","https://openalex.org/W4311212821","https://openalex.org/W1529660427","https://openalex.org/W2102065768","https://openalex.org/W4390752998","https://openalex.org/W2158578859","https://openalex.org/W4391020207"],"abstract_inverted_index":{"Sparse":[0],"connectivity":[1,27],"is":[2,36,100,116],"an":[3],"important":[4],"factor":[5],"behind":[6],"the":[7,22,50,69,72,76,96,103],"success":[8],"of":[9,24,47,81,110],"convolutional":[10],"neural":[11,15,30],"networks":[12,31],"and":[13,87,140],"recurrent":[14],"networks.":[16],"In":[17],"this":[18],"paper,":[19],"we":[20],"consider":[21],"problem":[23],"learning":[25],"sparse":[26],"for":[28,68],"feedforward":[29],"(FNNs).":[32],"The":[33,98,113],"key":[34],"idea":[35],"that":[37,54,83],"a":[38,44,64,89,118],"unit":[39,91],"should":[40],"be":[41],"connected":[42],"to":[43,62,78,106,126],"small":[45],"number":[46],"units":[48,70,82,105],"at":[49,71],"next":[51],"level":[52],"below":[53],"are":[55,84,144],"strongly":[56,85],"correlated.":[57],"We":[58],"use":[59,75],"Chow-Liu's":[60],"algorithm":[61],"learn":[63],"tree-structured":[65],"probabilistic":[66],"model":[67,115],"current":[73],"level,":[74],"tree":[77],"identify":[79],"subsets":[80],"correlated,":[86],"introduce":[88],"new":[90,104],"with":[92,136],"receptive":[93],"field":[94],"over":[95],"subsets.":[97],"procedure":[99],"repeated":[101],"on":[102],"build":[107],"multiple":[108],"layers":[109],"hidden":[111],"units.":[112],"resulting":[114],"called":[117],"TRF-net.":[119],"Empirical":[120],"results":[121],"show":[122],"that,":[123],"when":[124],"compared":[125],"dense":[127],"FNNs,":[128],"TRF-net":[129],"achieves":[130],"better":[131],"or":[132],"comparable":[133],"classification":[134],"performance":[135],"much":[137],"fewer":[138],"parameters":[139],"sparser":[141],"structures.":[142],"They":[143],"also":[145],"more":[146],"interpretable.":[147]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
