{"id":"https://openalex.org/W2602414261","doi":"https://doi.org/10.1109/tbdata.2017.2688372","title":"Distributed Sparse Class-Imbalance Learning and Its Applications","display_name":"Distributed Sparse Class-Imbalance Learning and Its Applications","publication_year":2017,"publication_date":"2017-03-28","ids":{"openalex":"https://openalex.org/W2602414261","doi":"https://doi.org/10.1109/tbdata.2017.2688372","mag":"2602414261"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2017.2688372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2017.2688372","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"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 Big Data","raw_type":"journal-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/A5035408769","display_name":"Chandresh Kumar Maurya","orcid":"https://orcid.org/0000-0003-3519-600X"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandresh Kumar Maurya","raw_affiliation_strings":["Department of Computer Science & Engineering, Indian Institute of Technology, Roorkee, Haridwar, U.K., India"],"raw_orcid":"https://orcid.org/0000-0003-3519-600X","affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Indian Institute of Technology, Roorkee, Haridwar, U.K., India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082753354","display_name":"Durga Toshniwal","orcid":null},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Durga Toshniwal","raw_affiliation_strings":["Department of Computer Science & Engineering, Indian Institute of Technology, Roorkee, Haridwar, U.K., India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Indian Institute of Technology, Roorkee, Haridwar, U.K., India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067653464","display_name":"Gopalan Vijendran Venkoparao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gopalan Vijendran Venkoparao","raw_affiliation_strings":["Research & Technology Center, Robert Bosch Engineering & Business Solution, Bangalore, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research & Technology Center, Robert Bosch Engineering & Business Solution, Bangalore, Karnataka, India","institution_ids":["https://openalex.org/I4210151956"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4548,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7395859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"7","issue":"5","first_page":"832","last_page":"844"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991000294685364,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991000294685364,"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/T12676","display_name":"Machine Learning and ELM","score":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.992900013923645,"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/coordinate-descent","display_name":"Coordinate descent","score":0.6171021461486816},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5364853143692017},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4898774027824402},{"id":"https://openalex.org/keywords/empirical-risk-minimization","display_name":"Empirical risk minimization","score":0.4176393151283264},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39507585763931274},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3875669836997986},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.34095650911331177},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.27591630816459656},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.10390880703926086}],"concepts":[{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.6171021461486816},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5364853143692017},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4898774027824402},{"id":"https://openalex.org/C107321475","wikidata":"https://www.wikidata.org/wiki/Q5374254","display_name":"Empirical risk minimization","level":2,"score":0.4176393151283264},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39507585763931274},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3875669836997986},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.34095650911331177},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27591630816459656},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.10390880703926086}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2017.2688372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2017.2688372","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"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 Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W728297","https://openalex.org/W85350352","https://openalex.org/W144837275","https://openalex.org/W167016754","https://openalex.org/W197274371","https://openalex.org/W218853445","https://openalex.org/W1525460779","https://openalex.org/W1558666744","https://openalex.org/W1563938718","https://openalex.org/W1580049798","https://openalex.org/W1922736325","https://openalex.org/W1955857676","https://openalex.org/W1960179861","https://openalex.org/W1966147156","https://openalex.org/W1970088130","https://openalex.org/W1980048347","https://openalex.org/W2000359198","https://openalex.org/W2007797768","https://openalex.org/W2038030840","https://openalex.org/W2051434435","https://openalex.org/W2071975988","https://openalex.org/W2095984592","https://openalex.org/W2107327607","https://openalex.org/W2114453181","https://openalex.org/W2116750654","https://openalex.org/W2117686388","https://openalex.org/W2118978333","https://openalex.org/W2120040939","https://openalex.org/W2123705108","https://openalex.org/W2125126592","https://openalex.org/W2131123062","https://openalex.org/W2131904035","https://openalex.org/W2134490011","https://openalex.org/W2139432235","https://openalex.org/W2143386126","https://openalex.org/W2143534004","https://openalex.org/W2148143831","https://openalex.org/W2152464310","https://openalex.org/W2153753709","https://openalex.org/W2157751754","https://openalex.org/W2158896888","https://openalex.org/W2164278908","https://openalex.org/W2164301055","https://openalex.org/W2165966284","https://openalex.org/W2198868857","https://openalex.org/W2209122160","https://openalex.org/W2284098035","https://openalex.org/W2338573124","https://openalex.org/W2405229368","https://openalex.org/W2616657226","https://openalex.org/W3001495003","https://openalex.org/W3006097074","https://openalex.org/W3009009611","https://openalex.org/W3012264151","https://openalex.org/W4245050711","https://openalex.org/W4292363360","https://openalex.org/W6603460400","https://openalex.org/W6605802503","https://openalex.org/W6606837198","https://openalex.org/W6631561801","https://openalex.org/W6634569365","https://openalex.org/W6640345655","https://openalex.org/W6657248855","https://openalex.org/W6678059977","https://openalex.org/W6679539681","https://openalex.org/W6680579697","https://openalex.org/W6681322979","https://openalex.org/W6682634173","https://openalex.org/W6683584131","https://openalex.org/W6683945318","https://openalex.org/W6687576168","https://openalex.org/W6713447996"],"related_works":["https://openalex.org/W2504004674","https://openalex.org/W2117229703","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W1595229445","https://openalex.org/W2939857954","https://openalex.org/W2894459442","https://openalex.org/W2097460654","https://openalex.org/W4286693783","https://openalex.org/W2144115358"],"abstract_inverted_index":{"In":[0],"the":[1,4,16,24,60,68,112,116,150,154,165,172],"present":[2],"work,":[3],"study":[5,176],"on":[6,119,137,180],"class":[7],"imbalance":[8],"problems":[9],"in":[10,15,94,178],"adistributedsetting":[11],"exploiting":[12],"sparsity":[13],"structure":[14],"data":[17,61,122],"has":[18],"been":[19],"carried":[20],"out.":[21],"We":[22,58,108],"formulate":[23],"class-imbalance":[25,161,177],"learning":[26,31],"problem":[27,32,47,70,101],"as":[28,158],"a":[29,39,72,104],"cost-sensitive":[30,35],"with$L_1$regularization.":[33],"The":[34,44,124],"loss":[36,75,80],"function":[37],"is":[38,48,83,102,127,171],"cost-weighted":[40],"smooth":[41,74],"hinge":[42],"loss.":[43],"resultant":[45],"optimization":[46],"minimized":[49],"within":[50],"theDistributed":[51],"Alternating":[52],"Direction":[53],"Method":[54],"of":[55,153,167],"Multiplier(DADMM)":[56],"framework.":[57],"partition":[59],"matrix":[62],"across":[63],"samples.":[64],"This":[65],"operation":[66],"splits":[67],"original":[69],"into":[71],"distributed$L_2$regularized":[73],"minimization":[76],"and":[77,89,139],"a$L_1$regularized":[78],"squared":[79],"minimization.$L_2$regularized":[81],"subproblem":[82],"solved":[84],"via":[85,129],"Limited-memory":[86],"Broyden-Fletcher-Goldfarb-Shanno":[87],"(L-BFGS)":[88],"random":[90],"coordinate":[91],"descent":[92],"method":[93],"parallel":[95],"at":[96],"multiple":[97],"processing":[98],"nodes":[99],"usingMPIwhereas$L_1$regularized":[100],"just":[103],"simple":[105],"soft-thresholding":[106],"operation.":[107],"show,":[109],"empirically,":[110],"that":[111],"distributed":[113],"solution":[114,118,126],"approximates":[115],"centralized":[117,125],"many":[120],"benchmark":[121,141],"sets.":[123],"obtained":[128],"Cost-Sensitive":[130],"Stochastic":[131],"Coordinate":[132],"Descent":[133],"(CSSCD).":[134],"Empirical":[135],"results":[136],"small":[138],"large-scale":[140],"datasets":[142],"show":[143],"some":[144],"promising":[145],"avenues":[146],"to":[147,175],"further":[148],"investigate":[149],"real-world":[151],"applications":[152],"proposed":[155],"algorithms":[156],"such":[157],"anomaly":[159],"detection,":[160],"learning,":[162],"etc.":[163],"To":[164],"best":[166],"our":[168],"knowledge,":[169],"ours":[170],"first":[173],"work":[174],"adistributedenvironment":[179],"large-scalesparsedata.":[181]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
