{"id":"https://openalex.org/W4401857369","doi":"https://doi.org/10.1145/3637528.3671981","title":"Mutual Distillation Extracting Spatial-temporal Knowledge for Lightweight Multi-channel Sleep Stage Classification","display_name":"Mutual Distillation Extracting Spatial-temporal Knowledge for Lightweight Multi-channel Sleep Stage Classification","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401857369","doi":"https://doi.org/10.1145/3637528.3671981"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671981","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5065497921","display_name":"Ziyu Jia","orcid":"https://orcid.org/0000-0002-8523-1419"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyu Jia","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025160246","display_name":"Haichao Wang","orcid":"https://orcid.org/0009-0002-1773-7343"},"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"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haichao Wang","raw_affiliation_strings":["Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030360404","display_name":"Yucheng Liu","orcid":"https://orcid.org/0000-0003-4738-0795"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yucheng Liu","raw_affiliation_strings":["University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103429920","display_name":"Tianzi Jiang","orcid":"https://orcid.org/0009-0006-9180-5024"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianzi Jiang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Science, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065497921"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"],"apc_list":null,"apc_paid":null,"fwci":1.8124,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.84721659,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1279","last_page":"1289"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10985","display_name":"Sleep and Wakefulness Research","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7506080865859985},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7318751215934753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5941573977470398},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5757935047149658},{"id":"https://openalex.org/keywords/sleep","display_name":"Sleep (system call)","score":0.5054738521575928},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47683635354042053},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4519582986831665},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.42973411083221436},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32588332891464233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11893332004547119},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1028672456741333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506080865859985},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7318751215934753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5941573977470398},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5757935047149658},{"id":"https://openalex.org/C2775841894","wikidata":"https://www.wikidata.org/wiki/Q4683692","display_name":"Sleep (system call)","level":2,"score":0.5054738521575928},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47683635354042053},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4519582986831665},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.42973411083221436},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32588332891464233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11893332004547119},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1028672456741333},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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":1,"locations":[{"id":"doi:10.1145/3637528.3671981","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1543113863","https://openalex.org/W1983256092","https://openalex.org/W2539353608","https://openalex.org/W2604096629","https://openalex.org/W2620998106","https://openalex.org/W2893892260","https://openalex.org/W2920016582","https://openalex.org/W2941679862","https://openalex.org/W2963140444","https://openalex.org/W2963919481","https://openalex.org/W2973069650","https://openalex.org/W2997006708","https://openalex.org/W3034369844","https://openalex.org/W3034795332","https://openalex.org/W3035993151","https://openalex.org/W3082394918","https://openalex.org/W3167917117","https://openalex.org/W3198543070","https://openalex.org/W4205949815","https://openalex.org/W4220772234","https://openalex.org/W4226426325","https://openalex.org/W4288391450","https://openalex.org/W4293143227","https://openalex.org/W4385768214","https://openalex.org/W4386928368","https://openalex.org/W4387969127","https://openalex.org/W4389317738"],"related_works":["https://openalex.org/W3026162553","https://openalex.org/W2768175398","https://openalex.org/W2344382886","https://openalex.org/W19111321","https://openalex.org/W2412887479","https://openalex.org/W3106607904","https://openalex.org/W32245304","https://openalex.org/W2953684491","https://openalex.org/W4285338581","https://openalex.org/W2015158429"],"abstract_inverted_index":{"Sleep":[0],"stage":[1,18,98],"classification":[2,99],"has":[3],"important":[4],"clinical":[5],"significance":[6],"for":[7,95],"the":[8,28,41,48,76,80,86,106,113,120,129,134,139,152,168,174,185,195,200],"diagnosis":[9],"of":[10,50,109,117],"sleep-related":[11],"diseases.":[12],"To":[13,84],"pursue":[14],"more":[15],"accurate":[16],"sleep":[17,21,52,82,97,118,186],"classification,":[19],"multi-channel":[20,51,81,96],"signals":[22],"are":[23,125],"widely":[24],"used":[25],"due":[26],"to":[27,36,63,127,199],"rich":[29,140],"spatial-temporal":[30,77,101,130,141,153],"information":[31],"contained.":[32],"However,":[33],"it":[34],"leads":[35],"a":[37,90],"great":[38],"increment":[39],"in":[40,79],"size":[42],"and":[43,74,112,122,158,176,193],"computational":[44],"costs,":[45],"which":[46],"constrain":[47],"application":[49],"models":[53,187],"on":[54,105,173],"hardware":[55],"devices.":[56],"Knowledge":[57],"distillation":[58,69,93,149],"is":[59],"an":[60],"effective":[61],"way":[62],"compress":[64],"models,":[65],"yet":[66],"existing":[67],"knowledge":[68,78,92,142,154],"methods":[70],"cannot":[71],"fully":[72],"extract":[73,128],"transfer":[75],"signals.":[83],"solve":[85],"problem,":[87],"we":[88],"propose":[89],"general":[91],"framework":[94,150,183],"called":[100],"mutual":[102,148],"distillation.":[103],"Based":[104],"spatial":[107,121],"relationship":[108],"human":[110],"body":[111],"temporal":[114,123],"transition":[115],"rules":[116],"signals,":[119],"modules":[124],"designed":[126],"knowledge,":[131],"thus":[132],"help":[133],"lightweight":[135],"student":[136,159,169],"model":[137,157,160],"learn":[138,162],"from":[143,163],"large-scale":[144],"teacher":[145],"model.":[146,170],"The":[147,171],"transfers":[151],"mutually.":[155],"Teacher":[156],"can":[161],"each":[164],"other,":[165],"further":[166],"improving":[167],"results":[172],"ISRUC-III":[175],"MASS-SS3":[177],"datasets":[178],"show":[179],"that":[180],"our":[181],"proposed":[182],"compresses":[184],"effectively":[188],"with":[189],"minimal":[190],"performance":[191,197],"loss":[192],"achieves":[194],"state-of-the-art":[196],"compared":[198],"baseline":[201],"methods.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}