{"id":"https://openalex.org/W3018278400","doi":"https://doi.org/10.1109/tpami.2020.2988262","title":"Learning Channel-Wise Interactions for Binary Convolutional Neural Networks","display_name":"Learning Channel-Wise Interactions for Binary Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3018278400","doi":"https://doi.org/10.1109/tpami.2020.2988262","mag":"3018278400","pmid":"https://pubmed.ncbi.nlm.nih.gov/32324540"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2020.2988262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.2988262","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100389366","display_name":"Ziwei Wang","orcid":"https://orcid.org/0000-0001-9225-8495"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziwei Wang","raw_affiliation_strings":["State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460385","display_name":"Jiwen Lu","orcid":"https://orcid.org/0000-0002-6121-5529"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwen Lu","raw_affiliation_strings":["State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100620306","display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0001-7701-234X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100389366"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.1397,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.93204787,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"43","issue":"10","first_page":"3432","last_page":"3445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7220152616500854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6788617372512817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6734236478805542},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6171061992645264},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5847707390785217},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5368457436561584},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5218937993049622},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.4831344783306122},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4723711311817169},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44594988226890564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3568895757198334},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.33473408222198486},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.22051897644996643},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15604233741760254}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7220152616500854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6788617372512817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6734236478805542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6171061992645264},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5847707390785217},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5368457436561584},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5218937993049622},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.4831344783306122},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4723711311817169},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44594988226890564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3568895757198334},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33473408222198486},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.22051897644996643},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15604233741760254},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2020.2988262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.2988262","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:32324540","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32324540","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G340251319","display_name":null,"funder_award_id":"61822603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4397514795","display_name":null,"funder_award_id":"U1813218","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5109092141","display_name":null,"funder_award_id":"61672306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6372554807","display_name":null,"funder_award_id":"U1713214","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7798227978","display_name":null,"funder_award_id":"JCYJ20170412170602564","funder_id":"https://openalex.org/F4320335803","funder_display_name":"Shenzhen Fundamental Research and Discipline Layout project"},{"id":"https://openalex.org/G867175025","display_name":null,"funder_award_id":"2017YFA0700802","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335803","display_name":"Shenzhen Fundamental Research and Discipline Layout project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":117,"referenced_works":["https://openalex.org/W1494114146","https://openalex.org/W1854404533","https://openalex.org/W1857884451","https://openalex.org/W1902934009","https://openalex.org/W2025768430","https://openalex.org/W2104636679","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2119144962","https://openalex.org/W2119717200","https://openalex.org/W2145339207","https://openalex.org/W2167215970","https://openalex.org/W2194775991","https://openalex.org/W2207374674","https://openalex.org/W2257979135","https://openalex.org/W2267635276","https://openalex.org/W2279098554","https://openalex.org/W2287328596","https://openalex.org/W2300242332","https://openalex.org/W2321627895","https://openalex.org/W2396990910","https://openalex.org/W2470394683","https://openalex.org/W2480418144","https://openalex.org/W2553303224","https://openalex.org/W2554592357","https://openalex.org/W2560017826","https://openalex.org/W2565639579","https://openalex.org/W2584265939","https://openalex.org/W2586654419","https://openalex.org/W2588860837","https://openalex.org/W2594829461","https://openalex.org/W2606433045","https://openalex.org/W2612445135","https://openalex.org/W2619307294","https://openalex.org/W2619890685","https://openalex.org/W2738318237","https://openalex.org/W2751842161","https://openalex.org/W2752037867","https://openalex.org/W2752782242","https://openalex.org/W2753301142","https://openalex.org/W2754084392","https://openalex.org/W2756085244","https://openalex.org/W2794791688","https://openalex.org/W2798463715","https://openalex.org/W2799171885","https://openalex.org/W2803281228","https://openalex.org/W2883780447","https://openalex.org/W2884150179","https://openalex.org/W2886851211","https://openalex.org/W2887447938","https://openalex.org/W2945908221","https://openalex.org/W2949267040","https://openalex.org/W2950248853","https://openalex.org/W2950614095","https://openalex.org/W2951829782","https://openalex.org/W2952899695","https://openalex.org/W2954048742","https://openalex.org/W2957777252","https://openalex.org/W2962716258","https://openalex.org/W2962872506","https://openalex.org/W2962950337","https://openalex.org/W2962965870","https://openalex.org/W2963037989","https://openalex.org/W2963114950","https://openalex.org/W2963150697","https://openalex.org/W2963177403","https://openalex.org/W2963262099","https://openalex.org/W2963286043","https://openalex.org/W2963341152","https://openalex.org/W2963363373","https://openalex.org/W2963420686","https://openalex.org/W2963424132","https://openalex.org/W2963547822","https://openalex.org/W2963559058","https://openalex.org/W2963723401","https://openalex.org/W2963791342","https://openalex.org/W2963979855","https://openalex.org/W2964008506","https://openalex.org/W2964118262","https://openalex.org/W2964133305","https://openalex.org/W2964299589","https://openalex.org/W2972443522","https://openalex.org/W3118608800","https://openalex.org/W4295262505","https://openalex.org/W4297775537","https://openalex.org/W4300081896","https://openalex.org/W6629438869","https://openalex.org/W6638992375","https://openalex.org/W6639703010","https://openalex.org/W6677580257","https://openalex.org/W6683826617","https://openalex.org/W6684563725","https://openalex.org/W6693397755","https://openalex.org/W6695314431","https://openalex.org/W6703271639","https://openalex.org/W6704665273","https://openalex.org/W6712112783","https://openalex.org/W6726275242","https://openalex.org/W6729788942","https://openalex.org/W6729956949","https://openalex.org/W6730047919","https://openalex.org/W6733472783","https://openalex.org/W6733877748","https://openalex.org/W6734215269","https://openalex.org/W6736368053","https://openalex.org/W6737664043","https://openalex.org/W6738693370","https://openalex.org/W6739000085","https://openalex.org/W6743912273","https://openalex.org/W6744495609","https://openalex.org/W6744700018","https://openalex.org/W6745722055","https://openalex.org/W6749737040","https://openalex.org/W6752089545","https://openalex.org/W6763207085","https://openalex.org/W6764383489","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2019977573","https://openalex.org/W2149980199","https://openalex.org/W3125766170","https://openalex.org/W2964954556"],"abstract_inverted_index":{"In":[0,59],"this":[1],"paper,":[2],"we":[3,64,94,158,182],"propose":[4,183],"a":[5,101,129,161,184],"channel-wise":[6,67,97,107,126,163,195,201],"interaction":[7,164],"based":[8,165],"binary":[9,19,32,45,81,166,190],"convolutional":[10,20,167],"neural":[11,21,168],"networks":[12,22,169],"(CI-BCNN)":[13],"approach":[14],"for":[15],"efficient":[16],"inference.":[17,92],"Conventional":[18],"usually":[23],"apply":[24],"the":[25,31,66,70,86,96,110,119,125,140,148,152,174,194,210,216,219],"xnor":[26],"and":[27,53,84,105,212,222],"bitcount":[28,187],"operations":[29],"in":[30,44,80,128,189,200],"convolution":[33,191],"with":[34,69,138],"notable":[35],"quantization":[36],"errors,":[37],"which":[38,73],"obtain":[39,151],"opposite":[40],"signs":[41,79,117],"of":[42,78,88,218],"pixels":[43],"feature":[46,82,112],"maps":[47,83,113],"compared":[48],"to":[49,55,75,114,150,172],"their":[50],"full-precision":[51],"counterparts":[52],"lead":[54],"significant":[56],"information":[57,87],"loss.":[58],"our":[60],"proposed":[61,220],"CI-BCNN":[62,123,221],"method,":[63],"exploit":[65],"interactions":[68,98,127,146],"prior":[71],"knowledge":[72],"aims":[74],"alleviate":[76],"inconsistency":[77],"preserves":[85],"input":[89],"samples":[90],"during":[91],"Specifically,":[93],"mine":[95],"by":[99,144,192],"using":[100],"reinforcement":[102,179],"learning":[103],"model,":[104],"impose":[106],"priors":[108,202],"on":[109,209],"intermediate":[111],"correct":[115],"inconsistent":[116],"through":[118],"interacted":[120,186],"bitcount.":[121],"Since":[122],"mines":[124],"large":[130],"search":[131,141,175],"space":[132,176],"where":[133],"each":[134],"channel":[135],"may":[136],"correlate":[137],"others,":[139],"deficiency":[142],"caused":[143],"sparse":[145],"obstacles":[147],"agent":[149],"optimal":[153],"policy.":[154],"To":[155],"address":[156],"this,":[157],"further":[159],"present":[160],"hierarchical":[162,178],"(HCI-BCNN)":[170],"method":[171],"shrink":[173],"via":[177],"learning.":[180],"Moreover,":[181],"denoising":[185],"operation":[188],"smoothing":[193],"interactions,":[196],"so":[197],"that":[198],"noise":[199],"can":[203],"be":[204],"alleviated.":[205],"Extensive":[206],"experimental":[207],"results":[208],"CIFAR-10":[211],"ImageNet":[213],"datasets":[214],"demonstrate":[215],"effectiveness":[217],"HCI-BCNN.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
