{"id":"https://openalex.org/W2936114877","doi":"https://doi.org/10.1109/icassp.2019.8682577","title":"Distribution Preserving Network Embedding","display_name":"Distribution Preserving Network Embedding","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2936114877","doi":"https://doi.org/10.1109/icassp.2019.8682577","mag":"2936114877"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682577","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682577","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5059839991","display_name":"Anyong Qin","orcid":"https://orcid.org/0000-0002-2538-822X"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anyong Qin","raw_affiliation_strings":["Chongqing University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052276737","display_name":"Zhaowei Shang","orcid":"https://orcid.org/0000-0002-1588-1387"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaowei Shang","raw_affiliation_strings":["Chongqing University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101664915","display_name":"Taiping Zhang","orcid":"https://orcid.org/0000-0001-9891-4203"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taiping Zhang","raw_affiliation_strings":["Chongqing University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085140523","display_name":"Yuan Yan Tang","orcid":"https://orcid.org/0000-0002-6887-130X"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Yuan Yan Tang","raw_affiliation_strings":["University of Macau, Macau, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"3562","last_page":"3566"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9955000281333923,"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":0.9936000108718872,"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/autoencoder","display_name":"Autoencoder","score":0.7927259206771851},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7196359634399414},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.670768141746521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6209529638290405},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.5570157170295715},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5435665845870972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5413787364959717},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5288887023925781},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49023348093032837},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.46167492866516113},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4407511055469513},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4190411865711212},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38369137048721313},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.29934418201446533},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25687769055366516}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7927259206771851},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7196359634399414},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.670768141746521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6209529638290405},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.5570157170295715},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5435665845870972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5413787364959717},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5288887023925781},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49023348093032837},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.46167492866516113},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4407511055469513},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4190411865711212},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38369137048721313},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29934418201446533},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25687769055366516},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8682577","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682577","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":36,"referenced_works":["https://openalex.org/W137735648","https://openalex.org/W166926187","https://openalex.org/W1902027874","https://openalex.org/W1998951954","https://openalex.org/W2022686119","https://openalex.org/W2067191022","https://openalex.org/W2072599882","https://openalex.org/W2073459066","https://openalex.org/W2100495367","https://openalex.org/W2102409316","https://openalex.org/W2108119513","https://openalex.org/W2120480077","https://openalex.org/W2133257461","https://openalex.org/W2136922672","https://openalex.org/W2148694408","https://openalex.org/W2154872931","https://openalex.org/W2162155934","https://openalex.org/W2189422931","https://openalex.org/W2207812465","https://openalex.org/W2533545350","https://openalex.org/W2562836854","https://openalex.org/W2608862709","https://openalex.org/W2751384800","https://openalex.org/W2804122900","https://openalex.org/W2964074409","https://openalex.org/W4205687621","https://openalex.org/W4250857377","https://openalex.org/W6606792154","https://openalex.org/W6668990524","https://openalex.org/W6675401909","https://openalex.org/W6679718588","https://openalex.org/W6682644385","https://openalex.org/W6685380521","https://openalex.org/W6728550200","https://openalex.org/W6730713231","https://openalex.org/W6776535907"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866","https://openalex.org/W2076182238"],"abstract_inverted_index":{"The":[0,113],"deep":[1,72],"autoencoder":[2],"network":[3],"which":[4,50,109],"is":[5,82],"based":[6],"on":[7,116],"constraining":[8],"non-negative":[9],"weights,":[10],"can":[11,30,51,75],"learn":[12,44],"a":[13,45,71,106],"low":[14,47],"dimensional":[15,48,60],"part-based":[16,73,107],"representation.":[17],"On":[18],"the":[19,22,26,34,37,53,58,79,96,99,111,122],"other":[20],"hand,":[21],"inherent":[23],"structure":[24,55],"of":[25,36,98,130],"each":[27],"data":[28,61,69,118],"cluster":[29,131],"be":[31,76],"described":[32],"by":[33,67],"distribution":[35,97],"intraclass":[38],"sample.":[39],"Then":[40],"one":[41],"hopes":[42],"to":[43,94],"new":[46],"feature":[49],"preserve":[52],"intrinsic":[54],"embedded":[56],"in":[57,128],"high":[59],"space":[62],"perfectly.":[63],"In":[64,89],"this":[65],"paper,":[66],"preserving":[68],"distribution,":[70],"representation":[74,108],"learned,":[77],"and":[78,102,133],"novel":[80],"algorithm":[81,124],"called":[83],"Distribution":[84],"Preserving":[85],"Network":[86],"Embedding":[87],"(DPNE).":[88],"DPNE,":[90],"we":[91,104],"first":[92],"need":[93],"estimate":[95],"original":[100],"data,":[101],"then":[103],"seek":[105],"respects":[110],"distribution.":[112],"experimental":[114],"results":[115],"real-world":[117],"sets":[119],"show":[120],"that":[121],"proposed":[123],"has":[125],"good":[126],"performance":[127],"terms":[129],"accuracy":[132],"adjusted":[134],"mutual":[135],"information":[136],"(AMI).":[137]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
