{"id":"https://openalex.org/W4405934961","doi":"https://doi.org/10.1109/tpami.2024.3524381","title":"Filter Pruning by High-Order Spectral Clustering","display_name":"Filter Pruning by High-Order Spectral Clustering","publication_year":2024,"publication_date":"2024-12-31","ids":{"openalex":"https://openalex.org/W4405934961","doi":"https://doi.org/10.1109/tpami.2024.3524381","pmid":"https://pubmed.ncbi.nlm.nih.gov/40030785"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3524381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3524381","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":null,"display_name":"Hang Lin","orcid":"https://orcid.org/0000-0003-2293-5344"},"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":"Hang Lin","raw_affiliation_strings":["BNRist, KLISS, School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"BNRist, KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101629182","display_name":"Yifan Peng","orcid":"https://orcid.org/0000-0003-0667-2599"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Peng","raw_affiliation_strings":["Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yubo Zhang","orcid":"https://orcid.org/0000-0003-3187-6227"},"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":"Yubo Zhang","raw_affiliation_strings":["BNRist, KLISS, School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"BNRist, KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047956564","display_name":"Lin Bie","orcid":"https://orcid.org/0000-0002-4844-1353"},"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":"Lin Bie","raw_affiliation_strings":["BNRist, KLISS, School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"BNRist, KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100773043","display_name":"Xibin Zhao","orcid":"https://orcid.org/0000-0002-6168-7016"},"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":"Xibin Zhao","raw_affiliation_strings":["BNRist, KLISS, School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"BNRist, KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100602494","display_name":"Yue Gao","orcid":"https://orcid.org/0000-0002-4971-590X"},"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":"Yue Gao","raw_affiliation_strings":["BNRist, KLISS, School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"BNRist, KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.7075,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87523287,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"47","issue":"4","first_page":"2402","last_page":"2415"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8777999877929688,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8777999877929688,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.8323000073432922,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.8267999887466431,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/pruning","display_name":"Pruning","score":0.6510372757911682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.649409294128418},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6416453719139099},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5654768347740173},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5199676752090454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4942753314971924},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4434187114238739},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3404920697212219},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.24749740958213806}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6510372757911682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.649409294128418},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6416453719139099},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5654768347740173},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5199676752090454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4942753314971924},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4434187114238739},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3404920697212219},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24749740958213806},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2024.3524381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3524381","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:40030785","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40030785","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/G2359401924","display_name":null,"funder_award_id":"L242167","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1977556410","https://openalex.org/W1996901117","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2773706593","https://openalex.org/W2796265726","https://openalex.org/W2798603777","https://openalex.org/W2886851211","https://openalex.org/W2894936553","https://openalex.org/W2894994475","https://openalex.org/W2924515500","https://openalex.org/W2928560789","https://openalex.org/W2962851801","https://openalex.org/W2963122961","https://openalex.org/W2963163009","https://openalex.org/W2963382930","https://openalex.org/W2964081807","https://openalex.org/W2964233199","https://openalex.org/W2964266063","https://openalex.org/W2976540144","https://openalex.org/W2984618279","https://openalex.org/W2997300524","https://openalex.org/W3034408420","https://openalex.org/W3034513523","https://openalex.org/W3034818206","https://openalex.org/W3088982929","https://openalex.org/W3116646121","https://openalex.org/W3173390350","https://openalex.org/W3180849877","https://openalex.org/W3181161645","https://openalex.org/W4285600325","https://openalex.org/W4285601858","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6677103964","https://openalex.org/W6678583879","https://openalex.org/W6683826617","https://openalex.org/W6684563725","https://openalex.org/W6685083254","https://openalex.org/W6720242923","https://openalex.org/W6724998850","https://openalex.org/W6725543821","https://openalex.org/W6726275242","https://openalex.org/W6730179637","https://openalex.org/W6732014465","https://openalex.org/W6733814495","https://openalex.org/W6737664043","https://openalex.org/W6739917289","https://openalex.org/W6748035112","https://openalex.org/W6751751081","https://openalex.org/W6755034786","https://openalex.org/W6755166560","https://openalex.org/W6755843862","https://openalex.org/W6770097211","https://openalex.org/W6771832129","https://openalex.org/W6772027524","https://openalex.org/W6774743274","https://openalex.org/W6779249178","https://openalex.org/W6783970114","https://openalex.org/W6787352875","https://openalex.org/W6787972765","https://openalex.org/W6790050307"],"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/W4229439743"],"abstract_inverted_index":{"Large":[0],"amount":[1],"of":[2,41],"redundancy":[3,14],"is":[4,23,180],"widely":[5],"present":[6],"in":[7,15,37,77,143],"convolutional":[8],"neural":[9],"networks":[10],"(CNNs).":[11],"Identifying":[12],"the":[13,16,20,29,42,49,127,136,140,159,181],"network":[17],"and":[18,84,114,138,151],"removing":[19],"redundant":[21,141],"filters":[22,119,137,142],"an":[24],"effective":[25],"way":[26],"to":[27,108,183],"compress":[28],"CNN":[30,78,149],"model":[31,58],"size":[32],"with":[33,165,173,187],"a":[34,92,169,189],"minimal":[35],"reduction":[36,172],"performance.":[38],"However,":[39],"most":[40],"existing":[43],"redundancy-based":[44],"pruning":[45,69,94,186],"methods":[46,70],"only":[47,57],"consider":[48],"distance":[50],"information":[51,117],"between":[52,61],"two":[53],"filters,":[54,113],"which":[55,179],"can":[56,131],"simple":[59],"correlations":[60,111],"filters.":[62],"Moreover,":[63],"we":[64,90,104,130,167],"point":[65],"out":[66],"that":[67,154],"distance-based":[68],"are":[71],"not":[72],"applicable":[73],"for":[74],"high-dimensional":[75],"features":[76],"models":[79,150],"by":[80,120],"our":[81,155],"experimental":[82],"observations":[83],"analysis.":[85],"To":[86],"tackle":[87],"this":[88,102],"issue,":[89],"propose":[91],"new":[93],"strategy":[95],"based":[96,125],"on":[97,126,135,147,177],"high-order":[98,116,128],"spectral":[99],"clustering.":[100],"In":[101],"approach,":[103],"use":[105],"hypergraph":[106,121],"structure":[107,122],"construct":[109],"complex":[110],"among":[112,118],"obtain":[115],"learning.":[123],"Finally,":[124],"information,":[129],"perform":[132],"better":[133],"clustering":[134],"remove":[139],"each":[144],"cluster.":[145],"Experiments":[146],"various":[148],"datasets":[152],"demonstrate":[153],"proposed":[156],"method":[157],"outperforms":[158],"recent":[160],"state-of-the-art":[161],"works.":[162],"For":[163],"example,":[164],"ResNet50,":[166],"achieve":[168,184],"57.1%":[170],"FLOPs":[171],"no":[174],"accuracy":[175],"drop":[176],"ImageNet,":[178],"first":[182],"lossless":[185],"such":[188],"high":[190],"compression":[191],"ratio.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}