{"id":"https://openalex.org/W4392903963","doi":"https://doi.org/10.1109/icassp48485.2024.10447229","title":"Importance of Negative Sampling in Weak Label Learning","display_name":"Importance of Negative Sampling in Weak Label Learning","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392903963","doi":"https://doi.org/10.1109/icassp48485.2024.10447229"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 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/A5108492825","display_name":"Ankit Shah","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ankit Shah","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062621920","display_name":"Tang Fuyu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fuyu Tang","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112705513","display_name":"Zelin Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zelin Ye","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102775511","display_name":"Rita Singh","orcid":"https://orcid.org/0000-0003-3743-0162"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rita Singh","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113017615","display_name":"Bhiksha Raj","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhiksha Raj","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,15213","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5108492825"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02612731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7530","last_page":"7534"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9983999729156494,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9983999729156494,"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/T11309","display_name":"Music and Audio Processing","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.983299970626831,"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/machine-learning","display_name":"Machine learning","score":0.7030256390571594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6646015644073486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.620910108089447},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6164693832397461},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.574212908744812},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5135884284973145}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7030256390571594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6646015644073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.620910108089447},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6164693832397461},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.574212908744812},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5135884284973145},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1968329810","https://openalex.org/W2140335411","https://openalex.org/W2194775991","https://openalex.org/W2354870669","https://openalex.org/W2593116425","https://openalex.org/W2768188490","https://openalex.org/W2798579254","https://openalex.org/W2905267911","https://openalex.org/W2936774411","https://openalex.org/W2948367246","https://openalex.org/W2970784940","https://openalex.org/W2998548481","https://openalex.org/W3003492572","https://openalex.org/W3080456792","https://openalex.org/W3098196327","https://openalex.org/W3103314642","https://openalex.org/W3118608800","https://openalex.org/W3123709248","https://openalex.org/W3136675874","https://openalex.org/W3205743929","https://openalex.org/W4287182412","https://openalex.org/W6668990524","https://openalex.org/W6686202851","https://openalex.org/W6687483927","https://openalex.org/W6745930336","https://openalex.org/W6750883802","https://openalex.org/W6763607942","https://openalex.org/W6767213273","https://openalex.org/W6787972765","https://openalex.org/W6789528441","https://openalex.org/W6791286331","https://openalex.org/W6795724354"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W2389015757","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Weak-label":[0],"learning":[1,8,87],"is":[2,29,56],"a":[3,47],"challenging":[4],"task":[5],"that":[6,60,77,103,123],"requires":[7],"from":[9,53],"data":[10],"\"bags\"":[11],"containing":[12],"positive":[13,33],"and":[14,88,98,101,110,131],"negative":[15,27,41,51,83,124],"instances,":[16,34],"but":[17],"only":[18],"the":[19,38,80,106,112],"bag":[20,55],"labels":[21],"are":[22,126],"known.":[23],"The":[24],"pool":[25],"of":[26,82],"instances":[28,52,84,125],"usually":[30],"larger":[31],"than":[32],"thus":[35],"making":[36],"selecting":[37,132],"most":[39],"informative":[40],"instance":[42],"critical":[43],"for":[44,50,66,85],"performance.":[45],"Such":[46],"selection":[48],"strategy":[49],"each":[54],"an":[57],"open":[58],"problem":[59],"has":[61],"not":[62,127],"been":[63],"well":[64],"studied":[65],"weak-label":[67,86,107,137],"learning.":[68,138],"In":[69],"this":[70],"paper,":[71],"we":[72],"study":[73],"several":[74],"sampling":[75,118],"strategies":[76],"can":[78,135],"measure":[79],"usefulness":[81],"select":[89],"them":[90,133],"accordingly.":[91],"We":[92],"test":[93],"our":[94],"method":[95],"on":[96],"CIFAR-10":[97],"AudioSet":[99],"datasets":[100],"show":[102],"it":[104],"improves":[105],"classification":[108],"performance":[109],"reduces":[111],"computational":[113],"cost":[114],"compared":[115],"to":[116],"random":[117],"methods.":[119],"Our":[120],"work":[121],"reveals":[122],"all":[128],"equally":[129],"irrelevant,":[130],"wisely":[134],"benefit":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}