{"id":"https://openalex.org/W2405602819","doi":"https://doi.org/10.1109/icassp.2016.7472146","title":"Empirically-estimable multi-class classification bounds","display_name":"Empirically-estimable multi-class classification bounds","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2405602819","doi":"https://doi.org/10.1109/icassp.2016.7472146","mag":"2405602819"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5072160392","display_name":"Alan Wisler","orcid":"https://orcid.org/0000-0003-2601-2846"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alan Wisler","raw_affiliation_strings":["Arizona State University ECEE and SHS"],"affiliations":[{"raw_affiliation_string":"Arizona State University ECEE and SHS","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021646973","display_name":"Visar Berisha","orcid":"https://orcid.org/0000-0001-8804-8874"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Visar Berisha","raw_affiliation_strings":["Arizona State University ECEE and SHS"],"affiliations":[{"raw_affiliation_string":"Arizona State University ECEE and SHS","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103053820","display_name":"Dennis Wei","orcid":"https://orcid.org/0000-0002-6510-1537"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dennis Wei","raw_affiliation_strings":["IBM Thomas J. Watson Research Center"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081874896","display_name":"Karthikeyan Natesan Ramamurthy","orcid":"https://orcid.org/0000-0002-6021-5930"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karthikeyan Ramamurthy","raw_affiliation_strings":["IBM Thomas J. Watson Research Center"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074371899","display_name":"Andreas Spanias","orcid":"https://orcid.org/0000-0003-0306-9348"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas Spanias","raw_affiliation_strings":["Arizona State University ECEE and SHS","SenSIP Center"],"affiliations":[{"raw_affiliation_string":"Arizona State University ECEE and SHS","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"SenSIP Center","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5072160392"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.8569,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.83257568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"53","issue":null,"first_page":"2594","last_page":"2598"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965999722480774,"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":0.9965999722480774,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9914000034332275,"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/T10057","display_name":"Face and Expression Recognition","score":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bhattacharyya-distance","display_name":"Bhattacharyya distance","score":0.7254543304443359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6568730473518372},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6313974261283875},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.6296204924583435},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.592308759689331},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5199588537216187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4862271845340729},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4592963755130768},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4519089460372925},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.429158091545105},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42473119497299194},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4111064672470093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34437495470046997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24484285712242126},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13389036059379578},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08547776937484741}],"concepts":[{"id":"https://openalex.org/C24145651","wikidata":"https://www.wikidata.org/wiki/Q2901249","display_name":"Bhattacharyya distance","level":2,"score":0.7254543304443359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6568730473518372},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6313974261283875},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.6296204924583435},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.592308759689331},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5199588537216187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4862271845340729},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4592963755130768},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4519089460372925},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.429158091545105},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42473119497299194},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4111064672470093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34437495470046997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24484285712242126},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13389036059379578},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08547776937484741},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W655565512","https://openalex.org/W1494922272","https://openalex.org/W1554663460","https://openalex.org/W1578859550","https://openalex.org/W1594031697","https://openalex.org/W1676820704","https://openalex.org/W1896038424","https://openalex.org/W1965864703","https://openalex.org/W2000149402","https://openalex.org/W2017337590","https://openalex.org/W2025890108","https://openalex.org/W2027390033","https://openalex.org/W2033207010","https://openalex.org/W2056500762","https://openalex.org/W2082571492","https://openalex.org/W2149197198","https://openalex.org/W2156642595","https://openalex.org/W2157791002","https://openalex.org/W2169090105","https://openalex.org/W3004533406","https://openalex.org/W3101241128","https://openalex.org/W4210694145","https://openalex.org/W4246227092","https://openalex.org/W6639447628","https://openalex.org/W6682953061"],"related_works":["https://openalex.org/W3149747767","https://openalex.org/W1536747792","https://openalex.org/W1982681402","https://openalex.org/W2192403599","https://openalex.org/W2366937720","https://openalex.org/W2163087802","https://openalex.org/W2155818328","https://openalex.org/W2121699558","https://openalex.org/W2145903892","https://openalex.org/W1982989375"],"abstract_inverted_index":{"In":[0,20],"this":[1,39,63],"paper,":[2],"we":[3,84],"extend":[4],"previously":[5],"developed":[6],"non-parametric":[7],"bounds":[8,36],"on":[9,97],"the":[10,23,35,58,87],"Bayes":[11],"risk":[12],"in":[13,38],"binary":[14],"classification":[15],"problems":[16],"to":[17,51,86],"multi-class":[18],"problems.":[19],"comparison":[21],"with":[22],"well-known":[24],"Bhattacharyya":[25],"bound":[26,64],"which":[27,83],"is":[28],"typically":[29],"calculated":[30],"by":[31,75],"employing":[32],"parametric":[33],"assumptions,":[34],"proposed":[37],"paper":[40],"are":[41],"directly":[42],"estimable":[43],"from":[44],"data,":[45],"provably":[46],"tighter,":[47],"and":[48,60,70],"more":[49],"robust":[50],"different":[52,93],"types":[53],"of":[54,62,90],"data.":[55,100],"We":[56],"verify":[57],"tightness":[59],"validity":[61],"using":[65],"an":[66],"illustrative":[67],"synthetic":[68],"example,":[69],"further":[71],"demonstrate":[72],"its":[73],"value":[74],"incorporating":[76],"it":[77],"into":[78],"a":[79],"feature":[80],"selection":[81],"algorithm":[82],"apply":[85],"real-world":[88],"problem":[89],"distinguishing":[91],"between":[92],"neuro-motor":[94],"disorders":[95],"based":[96],"sentence-level":[98],"speech":[99]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
