{"id":"https://openalex.org/W4408126114","doi":"https://doi.org/10.1145/3721293","title":"Compressing Deep Neural Networks with Goal-Specific Pruning and Self-Distillation","display_name":"Compressing Deep Neural Networks with Goal-Specific Pruning and Self-Distillation","publication_year":2025,"publication_date":"2025-03-04","ids":{"openalex":"https://openalex.org/W4408126114","doi":"https://doi.org/10.1145/3721293"},"language":"en","primary_location":{"id":"doi:10.1145/3721293","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3721293","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3721293","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3721293","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081986755","display_name":"Fuchen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Fa-You Chen","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066336388","display_name":"Yun-Jui Hsu","orcid":"https://orcid.org/0009-0001-7644-4068"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yun-Jui Hsu","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028318411","display_name":"Chia-Hsun Lu","orcid":"https://orcid.org/0009-0007-5966-8987"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chia-Hsun Lu","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, Taiwan","National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040050806","display_name":"Hong-Han Shuai","orcid":"https://orcid.org/0000-0003-2216-077X"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hong-Han Shuai","raw_affiliation_strings":["National Yang Ming Chiao Tung University, Hsinchu, Taiwan","National Yang Ming Chiao Tung University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"National Yang Ming Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006608753","display_name":"Lo\u2010Yao Yeh","orcid":"https://orcid.org/0000-0002-9764-0455"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Lo-Yao Yeh","raw_affiliation_strings":["Department of Information Management, National Central University, Zhongli District, Taoyuan, Taiwan","National Central University, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Information Management, National Central University, Zhongli District, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I22265921"]},{"raw_affiliation_string":"National Central University, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012064471","display_name":"Chih-Ya Shen","orcid":"https://orcid.org/0000-0002-0377-7945"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Ya Shen","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5081986755"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":7.4546,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.96286785,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"19","issue":"4","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976999759674072,"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":0.9976999759674072,"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":0.9976999759674072,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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/pruning","display_name":"Pruning","score":0.7596824169158936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6515135765075684},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6402800679206848},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5905211567878723},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5524524450302124},{"id":"https://openalex.org/keywords/goal-setting","display_name":"Goal setting","score":0.4799690246582031},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.478603333234787},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.47709470987319946},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15014714002609253},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11136394739151001},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09828603267669678},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.07038185000419617}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7596824169158936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6515135765075684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6402800679206848},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5905211567878723},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5524524450302124},{"id":"https://openalex.org/C2781195723","wikidata":"https://www.wikidata.org/wiki/Q199027","display_name":"Goal setting","level":2,"score":0.4799690246582031},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.478603333234787},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.47709470987319946},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15014714002609253},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11136394739151001},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09828603267669678},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.07038185000419617},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3721293","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3721293","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3721293","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3721293","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3721293","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3721293","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408126114.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W2050140640","https://openalex.org/W2108598243","https://openalex.org/W2137091430","https://openalex.org/W2143927862","https://openalex.org/W2153535241","https://openalex.org/W2170240176","https://openalex.org/W2565125333","https://openalex.org/W2593390416","https://openalex.org/W2605135468","https://openalex.org/W2739601332","https://openalex.org/W2775293244","https://openalex.org/W2782406413","https://openalex.org/W2805473054","https://openalex.org/W2896315416","https://openalex.org/W2928560789","https://openalex.org/W2962851801","https://openalex.org/W2963145730","https://openalex.org/W2963363373","https://openalex.org/W2964349401","https://openalex.org/W2965705320","https://openalex.org/W2965955046","https://openalex.org/W2981441441","https://openalex.org/W2982242214","https://openalex.org/W3010188086","https://openalex.org/W3012044667","https://openalex.org/W3034513523","https://openalex.org/W3035016149","https://openalex.org/W3035467254","https://openalex.org/W3093631941","https://openalex.org/W3127215335","https://openalex.org/W3168076195","https://openalex.org/W3173390350","https://openalex.org/W3175399856","https://openalex.org/W3186412620","https://openalex.org/W3208576249","https://openalex.org/W4205952419","https://openalex.org/W4206174637","https://openalex.org/W4223936353","https://openalex.org/W4226078332","https://openalex.org/W4249502209","https://openalex.org/W4287068746","https://openalex.org/W4290877352","https://openalex.org/W4290877962","https://openalex.org/W4300845283","https://openalex.org/W4301409532","https://openalex.org/W4382202914","https://openalex.org/W4408126114"],"related_works":["https://openalex.org/W2373300491","https://openalex.org/W2395294869","https://openalex.org/W2378744544","https://openalex.org/W2594301978","https://openalex.org/W2379704676","https://openalex.org/W1998810860","https://openalex.org/W4206442282","https://openalex.org/W2384505857","https://openalex.org/W2355171581","https://openalex.org/W2964217848"],"abstract_inverted_index":{"Neural":[0],"network":[1],"(NN)":[2],"compression":[3,172,191],"aims":[4],"at":[5],"reducing":[6,127],"the":[7,31,46,51,61,65,118,122,128,161,171,185],"model":[8,123,129],"size":[9,130],"and":[10,102,111,120,148,154,194],"receives":[11],"much":[12],"research":[13,137],"attention.":[14],"Nevertheless,":[15],"we":[16,57,78,133],"observe":[17,58],"that":[18,59,180],"when":[19],"compressing":[20,50,76],"convolutional":[21],"neural":[22,54],"networks":[23,55],"(CNNs),":[24],"previous":[25],"approaches":[26,182],"may":[27],"not":[28],"well":[29],"measure":[30],"impact":[32],"of":[33,131,190],"filters":[34],"to":[35,64,115,158,168],"loss,":[36],"resulting":[37],"in":[38,71,83,188],"a":[39,80,92,103,135,150,164],"significant":[40],"performance":[41],"degradation":[42],"after":[43],"compression.":[44,73],"On":[45],"other":[47],"hand,":[48],"for":[49,75,126],"fully":[52],"connected":[53],"(FCNNs),":[56],"converting":[60],"weight":[62],"matrix":[63],"block":[66,165],"diagonal":[67,166],"structure":[68,167],"would":[69],"result":[70],"better":[72],"Therefore,":[74],"CNNs,":[77],"propose":[79,149],"new":[81,93,136,151],"pipeline":[82],"this":[84],"article,":[85],"named":[86,96,108],"Retraining-Aware":[87],"Pruning":[88],"(RAP)":[89],",":[90,147],"with":[91,141],"self-distillation":[94],"approach,":[95],"High-Level":[97],"Activation-Guided":[98],"Attention-Preserving":[99],"Self-Distillation":[100],"(HAP)":[101],"novel":[104],"filter":[105],"pruning":[106],"strategy,":[107],"Normalized":[109],"Gradients":[110],"Geometric":[112],"Median":[113],"(NGGM)":[114],"effectively":[116,159],"improve":[117],"accuracy":[119],"reduce":[121],"size.":[124],"Further,":[125],"FCNNs,":[132],"formulate":[134],"problem,":[138],"i.e.,":[139],"Compression":[140,156],"Difference-Minimized":[142],"Block":[143],"Diagonal":[144],"Structure":[145],"(COMIS)":[146],"algorithm,":[152],"Memory-Efficient":[153],"Structure-Aware":[155],"(MESA)":[157],"prune":[160],"weights":[162],"into":[163],"significantly":[169,183],"boost":[170],"rate.":[173],"Extensive":[174],"experiments":[175],"on":[176],"different":[177],"models":[178],"show":[179],"our":[181],"outperform":[184],"state-of-the-art":[186],"baselines":[187],"terms":[189],"rate,":[192],"accuracy,":[193],"inference":[195],"speed-up.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}