{"id":"https://openalex.org/W3204477628","doi":"https://doi.org/10.1145/3490354.3494401","title":"Tradeoffs in streaming binary classification under limited inspection resources","display_name":"Tradeoffs in streaming binary classification under limited inspection resources","publication_year":2021,"publication_date":"2021-11-03","ids":{"openalex":"https://openalex.org/W3204477628","doi":"https://doi.org/10.1145/3490354.3494401","mag":"3204477628"},"language":"en","primary_location":{"id":"doi:10.1145/3490354.3494401","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490354.3494401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"preprint","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/A5027342655","display_name":"Parisa Hassanzadeh","orcid":"https://orcid.org/0000-0002-8236-0266"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Parisa Hassanzadeh","raw_affiliation_strings":["J.P. Morgan AI Research"],"affiliations":[{"raw_affiliation_string":"J.P. Morgan AI Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036538375","display_name":"Danial Dervovic","orcid":"https://orcid.org/0000-0002-6135-561X"},"institutions":[{"id":"https://openalex.org/I4210125307","display_name":"Morgan Stanley (United Kingdom)","ror":"https://ror.org/03csd5507","country_code":"GB","type":"company","lineage":["https://openalex.org/I2802755631","https://openalex.org/I4210125307"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Danial Dervovic","raw_affiliation_strings":["J.P. Morgan AI Research, London, UK"],"affiliations":[{"raw_affiliation_string":"J.P. Morgan AI Research, London, UK","institution_ids":["https://openalex.org/I4210125307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028847736","display_name":"Samuel Assefa","orcid":"https://orcid.org/0009-0005-6676-4497"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel Assefa","raw_affiliation_strings":["U.S. Bank AI Innovation"],"affiliations":[{"raw_affiliation_string":"U.S. Bank AI Innovation","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112298259","display_name":"P. Kiran Kumar Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prashant Reddy","raw_affiliation_strings":["J.P. Morgan AI Research"],"affiliations":[{"raw_affiliation_string":"J.P. Morgan AI Research","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057963205","display_name":"Manuela Veloso","orcid":"https://orcid.org/0000-0002-1995-095X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manuela Veloso","raw_affiliation_strings":["J.P. Morgan AI Research"],"affiliations":[{"raw_affiliation_string":"J.P. Morgan AI Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5027342655"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.1465851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/computer-science","display_name":"Computer science","score":0.8062601089477539},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.7121078372001648},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6597790122032166},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5649138689041138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5177323222160339},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5130109190940857},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.49771764874458313},{"id":"https://openalex.org/keywords/poisson-process","display_name":"Poisson process","score":0.4809679090976715},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4485777020454407},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.4444672763347626},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.433319091796875},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4256765842437744},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.19613662362098694},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1193149983882904}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8062601089477539},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.7121078372001648},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6597790122032166},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5649138689041138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5177323222160339},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5130109190940857},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.49771764874458313},{"id":"https://openalex.org/C166144826","wikidata":"https://www.wikidata.org/wiki/Q1145117","display_name":"Poisson process","level":3,"score":0.4809679090976715},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4485777020454407},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.4444672763347626},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.433319091796875},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4256765842437744},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.19613662362098694},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1193149983882904},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3490354.3494401","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490354.3494401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second ACM International Conference on AI in Finance","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1533970595","https://openalex.org/W1550064664","https://openalex.org/W1726806267","https://openalex.org/W1853481526","https://openalex.org/W1967252395","https://openalex.org/W1995231830","https://openalex.org/W2000051228","https://openalex.org/W2004499014","https://openalex.org/W2069293271","https://openalex.org/W2070645909","https://openalex.org/W2083774952","https://openalex.org/W2118978333","https://openalex.org/W2122770142","https://openalex.org/W2129301067","https://openalex.org/W2148143831","https://openalex.org/W2322524800","https://openalex.org/W2959792658","https://openalex.org/W2979172579","https://openalex.org/W2995260891","https://openalex.org/W3094604133","https://openalex.org/W3121934920","https://openalex.org/W3122167020","https://openalex.org/W3189128636","https://openalex.org/W3204796377"],"related_works":["https://openalex.org/W1978359496","https://openalex.org/W4366563794","https://openalex.org/W2084538642","https://openalex.org/W4236668082","https://openalex.org/W2387184232","https://openalex.org/W1979678609","https://openalex.org/W2884303440","https://openalex.org/W4236869226","https://openalex.org/W2072419078","https://openalex.org/W2904621566"],"abstract_inverted_index":{"Institutions":[0],"are":[1,43],"increasingly":[2],"relying":[3],"on":[4,12,97,137],"machine":[5],"learning":[6],"models":[7],"to":[8,27],"identify":[9],"and":[10,20,66,87,99,115,126,144,158],"alert":[11],"abnormal":[13],"events,":[14],"such":[15],"as":[16,82,119],"fraud,":[17],"cyber":[18],"attacks":[19],"system":[21],"failures.":[22],"These":[23],"alerts":[24],"often":[25],"need":[26],"be":[28,75],"manually":[29],"investigated":[30],"by":[31,45],"specialists.":[32],"Given":[33],"the":[34,40,79,108,111,116,123,127,134,146,159,164],"operational":[35],"cost":[36],"of":[37,71,122,161],"manual":[38],"inspections,":[39],"suspicious":[41,72,90],"events":[42,63,73],"selected":[44],"alerting":[46],"systems":[47],"with":[48,149],"carefully":[49],"designed":[50],"thresholds.":[51,101],"In":[52],"this":[53],"paper,":[54],"we":[55,105,153],"consider":[56],"an":[57],"imbalanced":[58],"binary":[59],"classification":[60],"problem,":[61],"where":[62],"arrive":[64],"sequentially":[65],"only":[67],"a":[68,83,120,138],"limited":[69],"number":[70],"can":[74],"inspected.":[76],"We":[77,132],"model":[78],"event":[80,91],"arrivals":[81],"non-homogeneous":[84],"Poisson":[85],"process,":[86],"compare":[88,145],"various":[89],"selection":[92,135],"methods":[93,136],"including":[94],"those":[95],"based":[96],"static":[98],"adaptive":[100],"For":[102],"each":[103],"method,":[104],"analytically":[106],"characterize":[107],"tradeoff":[109],"between":[110],"minority-class":[112],"detection":[113,142],"rate":[114],"inspection":[117],"capacity":[118],"function":[121],"class":[124,156],"imbalance":[125,157],"classifier":[128,162],"confidence":[129],"score":[130],"densities.":[131],"implement":[133],"real":[139],"public":[140],"fraud":[141],"dataset":[143],"empirical":[147],"results":[148],"analytical":[150],"bounds.":[151],"Finally,":[152],"investigate":[154],"how":[155],"choice":[160],"impact":[163],"tradeoff.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
