{"id":"https://openalex.org/W4386362974","doi":"https://doi.org/10.1109/tnnls.2023.3306512","title":"Block-Wise Partner Learning for Model Compression","display_name":"Block-Wise Partner Learning for Model Compression","publication_year":2023,"publication_date":"2023-09-01","ids":{"openalex":"https://openalex.org/W4386362974","doi":"https://doi.org/10.1109/tnnls.2023.3306512","pmid":"https://pubmed.ncbi.nlm.nih.gov/37656638"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3306512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3306512","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","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/A5056955447","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0002-6455-047X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-6455-047X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052163069","display_name":"Weiying Xie","orcid":"https://orcid.org/0000-0001-8310-024X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiying Xie","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-8310-024X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067798266","display_name":"Yunsong Li","orcid":"https://orcid.org/0000-0002-0234-6270"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunsong Li","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-0234-6270","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007285444","display_name":"Jie Lei","orcid":"https://orcid.org/0000-0003-0851-6565"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Lei","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-0851-6565","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101621262","display_name":"Kai Jiang","orcid":"https://orcid.org/0000-0001-9921-2043"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Jiang","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-9921-2043","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065061505","display_name":"Leyuan Fang","orcid":"https://orcid.org/0000-0003-2351-4461"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyuan Fang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-2351-4461","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033017179","display_name":"Qian Du","orcid":"https://orcid.org/0000-0001-8354-7500"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Du","raw_affiliation_strings":["Department of Electronic and Computer Engineering, Mississippi State University, Starkville, MS, USA"],"raw_orcid":"https://orcid.org/0000-0001-8354-7500","affiliations":[{"raw_affiliation_string":"Department of Electronic and Computer Engineering, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6526,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75151111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"35","issue":"12","first_page":"17582","last_page":"17595"},"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":0.9939000010490417,"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":0.9939000010490417,"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":0.9897000193595886,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9646000266075134,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7300179600715637},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6047999262809753},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.5969775319099426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4342672824859619},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.42049872875213623},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41907602548599243},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4183329939842224},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3847925066947937}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7300179600715637},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6047999262809753},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.5969775319099426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4342672824859619},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.42049872875213623},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41907602548599243},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4183329939842224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3847925066947937},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3306512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3306512","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37656638","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37656638","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2235370507","display_name":null,"funder_award_id":"QTZX23048","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4583694037","display_name":null,"funder_award_id":"U22B2014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5538951345","display_name":null,"funder_award_id":"62121001","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1980038761","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2577537809","https://openalex.org/W2592962403","https://openalex.org/W2808168148","https://openalex.org/W2886851211","https://openalex.org/W2924515500","https://openalex.org/W2928560789","https://openalex.org/W2942454403","https://openalex.org/W2963145730","https://openalex.org/W2963363373","https://openalex.org/W2963857746","https://openalex.org/W2970958999","https://openalex.org/W2984618279","https://openalex.org/W2990792015","https://openalex.org/W3033960544","https://openalex.org/W3034513523","https://openalex.org/W3034818206","https://openalex.org/W3034971973","https://openalex.org/W3035332806","https://openalex.org/W3093209609","https://openalex.org/W3100837220","https://openalex.org/W3107407793","https://openalex.org/W3113299742","https://openalex.org/W3137609883","https://openalex.org/W3138547151","https://openalex.org/W3139203094","https://openalex.org/W3148722043","https://openalex.org/W3168317852","https://openalex.org/W3171038842","https://openalex.org/W3173275561","https://openalex.org/W3173668541","https://openalex.org/W3176288137","https://openalex.org/W3177008256","https://openalex.org/W3180849877","https://openalex.org/W3181161645","https://openalex.org/W3185613252","https://openalex.org/W3185811833","https://openalex.org/W3212888835","https://openalex.org/W3214543237","https://openalex.org/W4200585832","https://openalex.org/W4220897963","https://openalex.org/W4226426325","https://openalex.org/W4310593159","https://openalex.org/W4313047887","https://openalex.org/W4318586146","https://openalex.org/W6633013443","https://openalex.org/W6726275242","https://openalex.org/W6737664043","https://openalex.org/W6748035112","https://openalex.org/W6749776392","https://openalex.org/W6752437554","https://openalex.org/W6755034786","https://openalex.org/W6761393460","https://openalex.org/W6762450006","https://openalex.org/W6762610423","https://openalex.org/W6779249178","https://openalex.org/W6789080154","https://openalex.org/W6792322516","https://openalex.org/W6798165038","https://openalex.org/W6802984017"],"related_works":["https://openalex.org/W3214662081","https://openalex.org/W2898360562","https://openalex.org/W4207000934","https://openalex.org/W2961085424","https://openalex.org/W4285140289","https://openalex.org/W3212328129","https://openalex.org/W3160421061","https://openalex.org/W3115525155","https://openalex.org/W3202154562","https://openalex.org/W4362663447"],"abstract_inverted_index":{"Despite":[0],"the":[1,12,44,59,66,73,101,105,111,113,128,143,146,150,153,169,175,191,199,229],"great":[2],"potential":[3],"of":[4,107,159,178,218],"convolutional":[5],"neural":[6],"networks":[7,53],"(CNNs)":[8],"in":[9,20,27,58,125],"various":[10],"tasks,":[11],"resource-hungry":[13],"nature":[14],"greatly":[15],"hinders":[16],"their":[17],"wide":[18],"deployment":[19],"cost-sensitive":[21],"and":[22,70,72,79,96,99,149,184,196],"low-powered":[23],"scenarios,":[24],"especially":[25],"applications":[26],"remote":[28],"sensing.":[29],"Existing":[30],"model":[31,103,129,172],"pruning":[32],"approaches,":[33],"implemented":[34],"by":[35],"a":[36,40,84,117,135,212],"\"subtraction\"":[37],"operation,":[38],"impose":[39],"performance":[41,63,123],"ceiling":[42],"on":[43,228],"slimmed":[45],"model.":[46],"Self-knowledge":[47],"distillation":[48],"(Self-KD)":[49],"resorts":[50],"to":[51,130,141],"auxiliary":[52],"that":[54,173],"are":[55],"only":[56,221],"active":[57],"training":[60],"phase":[61],"for":[62,119,122,226],"improvement.":[64],"However,":[65],"knowledge":[67,75],"is":[68,77,139,155,236],"holistic":[69],"crude,":[71],"learning-based":[74],"transfer":[76],"mediate":[78],"lossy.":[80],"Here,":[81],"we":[82,165],"propose":[83],"novel":[85],"model-compression":[86,206],"method,":[87],"termed":[88],"block-wise":[89],"partner":[90,118,154],"learning":[91],"(BPL),":[92],"which":[93],"comprises":[94],"\"extension\"":[95],"\"fusion\"":[97],"operations":[98,215],"liberates":[100],"compressed":[102,171],"from":[104,110],"bondage":[106],"baseline.":[108],"Different":[109],"Self-KD,":[112],"proposed":[114],"BPL":[115,200],"creates":[116],"each":[120],"block":[121,148],"enhancement":[124,176],"training.":[126],"For":[127,208],"absorb":[131],"more":[132],"diverse":[133],"information,":[134],"diversity":[136],"loss":[137,225],"(DL)":[138],"designed":[140],"evaluate":[142],"difference":[144],"between":[145],"original":[147],"partner.":[151],"Besides,":[152],"fused":[156,170],"equivalently":[157],"instead":[158],"being":[160],"discarded":[161],"directly.":[162],"After":[163],"training,":[164],"can":[166],"simply":[167],"adopt":[168],"contains":[174],"information":[177],"partners":[179],"but":[180],"with":[181,220],"fewer":[182],"parameters":[183],"less":[185],"inference":[186],"cost.":[187],"As":[188],"validated":[189],"using":[190],"UC":[192,230],"Merced":[193,231],"land-use,":[194],"NWPU-RESISC45,":[195],"RSD46-WHU":[197],"datasets,":[198],"demonstrates":[201],"superiority":[202],"over":[203],"other":[204],"compared":[205],"approaches.":[207],"example,":[209],"it":[210],"attains":[211],"substantial":[213],"floating-point":[214],"(FLOPs)":[216],"reduction":[217],"73.97%":[219],"0.24":[222],"accuracy":[223],"(ACC.)":[224],"ResNet-50":[227],"land-use":[232],"dataset.":[233],"The":[234],"code":[235],"available":[237],"at":[238],"https://github.com/zhangxin-xd/BPL.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
