{"id":"https://openalex.org/W7124428640","doi":"https://doi.org/10.1109/tpami.2026.3653780","title":"Non-Gradient Hash Factor Learning for High-Dimensional and Incomplete Data Representation Learning","display_name":"Non-Gradient Hash Factor Learning for High-Dimensional and Incomplete Data Representation Learning","publication_year":2026,"publication_date":"2026-01-16","ids":{"openalex":"https://openalex.org/W7124428640","doi":"https://doi.org/10.1109/tpami.2026.3653780","pmid":"https://pubmed.ncbi.nlm.nih.gov/41543949"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2026.3653780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3653780","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":"https://openalex.org/A5123223986","display_name":"Di Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wu","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7788-9202","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009043043","display_name":"S. Samuel Li","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihui Li","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yi He","orcid":"https://orcid.org/0000-0002-5357-6623"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi He","raw_affiliation_strings":["Department of Data Science, William &amp; Mary, Williamsburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5357-6623","affiliations":[{"raw_affiliation_string":"Department of Data Science, William &amp; Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123247331","display_name":"Xin Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Luo","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-1348-5305","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123240730","display_name":"Xinbo Gao","orcid":null},"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":"Xinbo Gao","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-7985-0037","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":38.715,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.99737888,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"48","issue":"5","first_page":"5811","last_page":"5826"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.14880000054836273,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.14880000054836273,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.1354999989271164,"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/T14347","display_name":"Big Data and Digital Economy","score":0.11810000240802765,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/hash-function","display_name":"Hash function","score":0.7085000276565552},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5015000104904175},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4902999997138977},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4803999960422516},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.4309999942779541},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.40310001373291016},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3880999982357025},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.37549999356269836}],"concepts":[{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7085000276565552},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6297000050544739},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5407999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5327000021934509},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5015000104904175},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4902999997138977},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4803999960422516},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.4309999942779541},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.40310001373291016},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3977999985218048},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3880999982357025},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.37549999356269836},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37040001153945923},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.3357999920845032},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.3199999928474426},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2809000015258789},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C145671259","wikidata":"https://www.wikidata.org/wiki/Q1493786","display_name":"Discrete optimization","level":3,"score":0.26409998536109924}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2026.3653780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3653780","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:41543949","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41543949","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6797351241111755}],"awards":[{"id":"https://openalex.org/G189390890","display_name":null,"funder_award_id":"62576289","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8515641209","display_name":null,"funder_award_id":"62272078","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"High-dimensional":[0],"and":[1,17,40,93,163,170],"incomplete":[2],"(HDI)":[3],"data":[4,34,235],"are":[5],"ubiquitous":[6],"in":[7,82],"various":[8],"Big":[9],"Data-related":[10],"industrial":[11],"applications,":[12],"such":[13],"as":[14],"drug":[15],"innovation":[16],"recommender":[18],"systems.":[19],"Hash-learning":[20],"is":[21,79,224],"the":[22,56,61,68,72,119,130,142,149,174],"most":[23],"efficient":[24,162],"representation":[25,183,200,236],"learning":[26,47,151,184,219],"approach":[27,48],"to":[28,36,54,75,117,146,187,196,201,227],"extract":[29],"hidden":[30],"information":[31],"from":[32],"HDI":[33,87,157,202,234],"owing":[35],"its":[37,161,222],"fast":[38],"reasoning":[39],"low":[41],"storage.":[42],"However,":[43],"an":[44,136],"existing":[45],"hash":[46,65,101,218],"commonly":[49],"employs":[50],"gradient-based":[51],"optimization":[52,121],"techniques":[53],"address":[55],"discrete":[57,111,138,150],"objective":[58,152],"caused":[59],"by":[60,90],"binary":[62,76,126,199],"nature":[63],"of":[64,125,153,176,189,229],"factors,":[66],"where":[67],"Quantization":[69,168],"(i.e.,":[70],"quantizing":[71],"real":[73],"values":[74],"codes)":[77],"loss":[78,84],"inevitable,":[80],"resulting":[81],"accuracy":[83,223],"when":[85],"representing":[86],"data.":[88,203],"Motivated":[89],"these":[91],"critical":[92],"vital":[94],"issues,":[95],"this":[96],"paper":[97],"proposes":[98],"a":[99,110,190,230],"non-gradient":[100],"factor":[102],"(NGHF)":[103],"model":[104,232],"with":[105],"three-fold":[106],"ideas:":[107],"a)":[108],"innovating":[109],"differential":[112],"evolution":[113],"(DDE)":[114],"algorithm":[115,145],"able":[116,195],"simulate":[118],"continuous":[120],"via":[122],"disabling":[123],"bits":[124],"codes":[127],"based":[128],"on":[129,156,207],"projected":[131],"Hamming":[132],"dissimilarity,":[133],"thus":[134],"enabling":[135],"effective":[137],"optimizer,":[139],"b)":[140],"applying":[141],"proposed":[143],"DDE":[144],"directly":[147],"optimize":[148],"NGHF":[154,180,213],"defined":[155],"data,":[158],"thereby":[159],"facilitating":[160],"precise":[164,198],"training":[165],"without":[166],"any":[167],"loss,":[169],"c)":[171],"theoretically":[172],"proving":[173],"convergence":[175],"NGHF.":[177],"As":[178],"such,":[179],"possesses":[181],"high":[182],"ability":[185],"comparable":[186,226],"that":[188,212,228],"real-valued":[191,231],"model,":[192],"making":[193],"it":[194],"achieve":[197],"Extensive":[204],"experimental":[205],"results":[206],"nine":[208],"real-world":[209],"datasets":[210],"demonstrate":[211],"significantly":[214],"outperforms":[215],"eight":[216],"state-of-the-art":[217],"models.":[220],"Moreover,":[221],"amazingly":[225],"for":[233],"learning.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":5}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-01-17T00:00:00"}
