{"id":"https://openalex.org/W4392746589","doi":"https://doi.org/10.1109/tnnls.2024.3373609","title":"Playing the Lottery With Concave Regularizers for Sparse Trainable Neural Networks","display_name":"Playing the Lottery With Concave Regularizers for Sparse Trainable Neural Networks","publication_year":2024,"publication_date":"2024-03-13","ids":{"openalex":"https://openalex.org/W4392746589","doi":"https://doi.org/10.1109/tnnls.2024.3373609","pmid":"https://pubmed.ncbi.nlm.nih.gov/38478446"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3373609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3373609","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5062328236","display_name":"Giulia Fracastoro","orcid":"https://orcid.org/0000-0001-8495-1097"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Giulia Fracastoro","raw_affiliation_strings":["Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082948079","display_name":"Sophie M. Fosson","orcid":"https://orcid.org/0000-0003-2316-7404"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sophie M. Fosson","raw_affiliation_strings":["Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018841739","display_name":"Andrea Migliorati","orcid":"https://orcid.org/0000-0001-9239-0568"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Migliorati","raw_affiliation_strings":["Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041746196","display_name":"Giuseppe C. Calafiore","orcid":"https://orcid.org/0000-0002-6428-5653"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe C. Calafiore","raw_affiliation_strings":["Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications (DET), Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5062328236"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":1.1861,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71968201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"36","issue":"3","first_page":"4575","last_page":"4585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization 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/T10057","display_name":"Face and Expression Recognition","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.7348725199699402},{"id":"https://openalex.org/keywords/lottery","display_name":"Lottery","score":0.713625967502594},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6634821891784668},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5474454164505005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49810123443603516},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4850970506668091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48404544591903687},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4371935725212097},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35936877131462097},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3275929093360901},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17987850308418274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348725199699402},{"id":"https://openalex.org/C2777340749","wikidata":"https://www.wikidata.org/wiki/Q6684955","display_name":"Lottery","level":2,"score":0.713625967502594},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6634821891784668},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5474454164505005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49810123443603516},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4850970506668091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48404544591903687},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4371935725212097},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35936877131462097},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3275929093360901},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17987850308418274},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3373609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3373609","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38478446","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38478446","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1497748561","https://openalex.org/W1820680895","https://openalex.org/W1965125844","https://openalex.org/W1969387119","https://openalex.org/W2007339694","https://openalex.org/W2012961725","https://openalex.org/W2107861471","https://openalex.org/W2135046866","https://openalex.org/W2295652899","https://openalex.org/W2554302513","https://openalex.org/W2620850570","https://openalex.org/W2808168148","https://openalex.org/W2886697509","https://openalex.org/W2886851211","https://openalex.org/W2924515500","https://openalex.org/W2928560789","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963145730","https://openalex.org/W3033960544","https://openalex.org/W3034234149","https://openalex.org/W3034513523","https://openalex.org/W3035467254","https://openalex.org/W3098306969","https://openalex.org/W3098595037","https://openalex.org/W3116646121","https://openalex.org/W3119228957","https://openalex.org/W3166460952","https://openalex.org/W3168076195","https://openalex.org/W3168317852","https://openalex.org/W4213080446","https://openalex.org/W4226060263","https://openalex.org/W6677103964","https://openalex.org/W6682433143","https://openalex.org/W6726275242","https://openalex.org/W6739917289","https://openalex.org/W6745148473","https://openalex.org/W6751979845","https://openalex.org/W6755034786","https://openalex.org/W6755843862","https://openalex.org/W6767327937","https://openalex.org/W6771450561","https://openalex.org/W6771793280","https://openalex.org/W6772453130","https://openalex.org/W6773423997","https://openalex.org/W6774302960","https://openalex.org/W6779249178","https://openalex.org/W6783955940","https://openalex.org/W6803476328"],"related_works":["https://openalex.org/W2004731113","https://openalex.org/W1556639976","https://openalex.org/W2366147166","https://openalex.org/W2394167907","https://openalex.org/W2139765960","https://openalex.org/W2128949092","https://openalex.org/W2357035722","https://openalex.org/W2066997075","https://openalex.org/W2368351749","https://openalex.org/W2358800538"],"abstract_inverted_index":{"The":[0,26,91,124],"design":[1],"of":[2,7,13,28,61,67,93,118,130,137,152,181],"sparse":[3,29,80],"neural":[4],"networks,":[5],"i.e.,":[6,100],"networks":[8],"with":[9],"a":[10,52,115,138],"reduced":[11],"number":[12],"parameters,":[14],"has":[15],"been":[16],"attracting":[17],"increasing":[18],"research":[19],"attention":[20],"in":[21,39,89,156],"the":[22,34,40,46,59,62,68,98,122,128,135,144,150,153,157,174,179],"last":[23],"few":[24],"years.":[25],"use":[27,129],"models":[30],"may":[31],"significantly":[32],"reduce":[33],"computational":[35],"and":[36,169],"storage":[37],"footprint":[38],"inference":[41,63],"phase.":[42,70],"In":[43,110],"this":[44,111],"context,":[45],"lottery":[47],"ticket":[48],"hypothesis":[49],"(LTH)":[50],"constitutes":[51],"breakthrough":[53],"result,":[54],"that":[55,73,85,171,173],"addresses":[56],"not":[57],"only":[58],"performance":[60,180],"phase,":[64],"but":[65],"also":[66],"training":[69],"It":[71],"states":[72],"it":[74],"is":[75,105,127],"possible":[76],"to":[77,96,101,120,133],"extract":[78],"effective":[79,94],"subnetworks,":[81],"called":[82],"winning":[83,103],"tickets,":[84,104],"can":[86,177],"be":[87],"trained":[88],"isolation.":[90],"development":[92],"methods":[95,119],"play":[97,121],"lottery,":[99],"find":[102],"still":[106],"an":[107],"open":[108],"problem.":[109],"article,":[112],"we":[113,161],"propose":[114,162],"novel":[116],"class":[117],"lottery.":[123],"key":[125],"point":[126],"concave":[131],"regularization":[132],"promote":[134],"sparsity":[136],"relaxed":[139],"binary":[140],"mask,":[141],"which":[142],"represents":[143],"network":[145],"topology.":[146],"We":[147],"theoretically":[148],"analyze":[149],"effectiveness":[151],"proposed":[154,175],"method":[155,176],"convex":[158],"framework.":[159],"Then,":[160],"extended":[163],"numerical":[164],"tests":[165],"on":[166],"various":[167],"datasets":[168],"architectures,":[170],"show":[172],"improve":[178],"state-of-the-art":[182],"algorithms.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}