{"id":"https://openalex.org/W4402744232","doi":"https://doi.org/10.1007/s10994-024-06618-8","title":"Explaining outliers and anomalous groups via subspace density contrastive loss","display_name":"Explaining outliers and anomalous groups via subspace density contrastive loss","publication_year":2024,"publication_date":"2024-09-23","ids":{"openalex":"https://openalex.org/W4402744232","doi":"https://doi.org/10.1007/s10994-024-06618-8"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-024-06618-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-024-06618-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-024-06618-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-024-06618-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075369704","display_name":"Fabrizio Angiulli","orcid":"https://orcid.org/0000-0002-9860-7569"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Fabrizio Angiulli","raw_affiliation_strings":["DIMES, University of Calabria, Rende, Italy"],"affiliations":[{"raw_affiliation_string":"DIMES, University of Calabria, Rende, Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090380495","display_name":"Fabio Fassetti","orcid":null},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Fassetti","raw_affiliation_strings":["DIMES, University of Calabria, Rende, Italy"],"affiliations":[{"raw_affiliation_string":"DIMES, University of Calabria, Rende, Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036911190","display_name":"Simona Nistic\u00f2","orcid":"https://orcid.org/0000-0002-7386-2512"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Simona Nistic\u00f2","raw_affiliation_strings":["DIMES, University of Calabria, Rende, Italy"],"affiliations":[{"raw_affiliation_string":"DIMES, University of Calabria, Rende, Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055479421","display_name":"Luigi Palopoli","orcid":"https://orcid.org/0000-0003-4915-5137"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luigi Palopoli","raw_affiliation_strings":["DIMES, University of Calabria, Rende, Italy"],"affiliations":[{"raw_affiliation_string":"DIMES, University of Calabria, Rende, Italy","institution_ids":["https://openalex.org/I45204951"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075369704"],"corresponding_institution_ids":["https://openalex.org/I45204951"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.4464,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85053629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"113","issue":"10","first_page":"7565","last_page":"7589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7949092388153076},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.698184609413147},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45273202657699585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44757986068725586},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4179234802722931},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36124899983406067},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3558643162250519}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7949092388153076},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.698184609413147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45273202657699585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44757986068725586},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4179234802722931},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36124899983406067},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3558643162250519}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10994-024-06618-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-024-06618-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-024-06618-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10994-024-06618-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-024-06618-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-024-06618-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324136","display_name":"Universit\u00e0 della Calabria","ror":"https://ror.org/02rc97e94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402744232.pdf","grobid_xml":"https://content.openalex.org/works/W4402744232.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W199035648","https://openalex.org/W1673310716","https://openalex.org/W1965606617","https://openalex.org/W1966809779","https://openalex.org/W1966836840","https://openalex.org/W1991758224","https://openalex.org/W1999518899","https://openalex.org/W2000661457","https://openalex.org/W2038819732","https://openalex.org/W2067092965","https://openalex.org/W2103378897","https://openalex.org/W2120236791","https://openalex.org/W2129905273","https://openalex.org/W2167717760","https://openalex.org/W2169930371","https://openalex.org/W2294019357","https://openalex.org/W2294798173","https://openalex.org/W2296719434","https://openalex.org/W2316630624","https://openalex.org/W2533835508","https://openalex.org/W2740746404","https://openalex.org/W2774228929","https://openalex.org/W2783205364","https://openalex.org/W2785362611","https://openalex.org/W2896680395","https://openalex.org/W2899072250","https://openalex.org/W2910965336","https://openalex.org/W2962819609","https://openalex.org/W2963130695","https://openalex.org/W3040266635","https://openalex.org/W3085114395","https://openalex.org/W3097094324","https://openalex.org/W3098957257","https://openalex.org/W3111802945","https://openalex.org/W3135550350","https://openalex.org/W3141335229","https://openalex.org/W3168527239","https://openalex.org/W4205471456","https://openalex.org/W4210457304","https://openalex.org/W4213374550","https://openalex.org/W4225150645","https://openalex.org/W4241828375","https://openalex.org/W4293657497","https://openalex.org/W4387430237"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W1861706286","https://openalex.org/W2219338811","https://openalex.org/W2149583853","https://openalex.org/W1995723671","https://openalex.org/W2164647769","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Abstract":[0],"Explainable":[1],"AI":[2],"refers":[3],"to":[4,21,48,76,80,97,103,133,141,165],"techniques":[5],"by":[6,13,176,204,214],"which":[7,71,239],"the":[8,26,78,100,108,111,122,143,186,189,194,198,201,205,210,215,224,230,236,270,273],"reasons":[9],"underlying":[10],"decisions":[11],"taken":[12],"intelligent":[14],"artifacts":[15],"are":[16],"single":[17],"out":[18,58,213],"and":[19,93,127,159,260,264],"provided":[20,250],"users.":[22],"Outlier":[23],"detection":[24],"is":[25,102,174,243],"task":[27],"of":[28,70,110,118,121,131,169,188,200,226,248,272],"individuating":[29],"anomalous":[30],"objects":[31],"within":[32,209],"a":[33,45,51,73,89,119,150,155,240,246,265],"given":[34,52,86],"data":[35,53,91,262],"population":[36,92],"they":[37],"belong":[38],"to.":[39],"In":[40],"this":[41],"paper":[42,148],"we":[43],"propose":[44],"new":[46],"technique":[47,64],"explain":[49],"why":[50],"object":[54,95,144],"has":[55],"been":[56],"singled":[57,212],"as":[59],"anomalous.":[60],"The":[61,147,171],"explanation":[62,116,242],"our":[63],"returns":[65],"also":[66,222,235],"includes":[67],"counterfactuals,":[68],"each":[69],"denotes":[72],"possible":[74,105],"way":[75],"\u201crepair\u201d":[77],"outlier":[79,191],"make":[81,142],"it":[82],"an":[83,94,115,128,177],"inlier.":[84],"Thus,":[85],"in":[87,139,163,229,238,252],"input":[88,112,190],"reference":[90],"deemed":[96],"be":[98,134],"anomalous,":[99],"aim":[101],"provide":[104],"explanations":[106],"for":[107,245],"anomaly":[109],"object,":[113],"where":[114],"consists":[117],"subset":[120],"features,":[123],"called":[124,136],"choice":[125,157,217],",":[126,138],"associated":[129],"set":[130],"changes":[132],"applied,":[135],"mask":[137,160,195,202,206],"order":[140,164],"\u201cbehave":[145],"normally\u201d.":[146],"presents":[149],"deep":[151],"learning":[152,172],"architecture":[153],"exploiting":[154],"features":[156,216,227],"module":[158,162],"generation":[161,207],"learn":[166],"both":[167,258],"components":[168],"explanations.":[170],"procedure":[173],"guided":[175],"ad-hoc":[178],"loss":[179],"function":[180],"that":[181,220],"simultaneously":[182],"maximizes":[183],"(minimizes,":[184],"resp.)":[185],"isolation":[187],"before":[192],"applying":[193],"(resp.,":[196],"after":[197],"application":[199],"returned":[203],"module)":[208],"subspace":[211],"module,":[218],"all":[219],"while":[221],"minimizing":[223],"number":[225],"involved":[228],"selected":[231],"choice.":[232],"We":[233,254],"consider":[234],"case":[237],"common":[241],"required":[244],"group":[247],"outliers":[249],"together":[251],"input.":[253],"present":[255],"experiments":[256],"on":[257],"artificial":[259],"real":[261],"sets":[263],"comparison":[266],"with":[267],"competitors":[268],"validating":[269],"effectiveness":[271],"proposed":[274],"approach.":[275]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-10T14:07:55.174380","created_date":"2025-10-10T00:00:00"}